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Purpose: This paper aims to develop a method for tuning the parameters of the active disturbance rejection controller (ADRC) for fixed-wing unmanned aerial vehicles (UAVs). The bald eagle search (BES) algorithm has been improved, and a cost function has been designed to enhance the optimization efficiency of ADRC parameters. Design/methodology/approach: A six-degree-of-freedom nonlinear model for a fixed-wing UAV has been developed, and its attitude controller has been formulated using the active disturbance rejection control method. The parameters of the disturbance rejection controller have been fine-tuned using the collaborative mutual promotion bald eagle search (CMP-BES) algorithm. The pitch and roll controllers for the UAV have been individually optimized to obtain the most effective controller parameters. Findings: Inspired by the salp swarm algorithm (SSA), the interaction among individual eagles has been incorporated into the CMP-BES algorithm, thereby enhancing the algorithm's exploration capability. The efficient and accurate optimization ability of the proposed algorithm has been demonstrated through comparative experiments with genetic algorithm, particle swarm optimization, Harris hawks optimization HHO, BES and modified bald eagle search algorithms. The algorithm's capability to solve complex optimization problems has been further proven by testing on the CEC2017 test function suite. A transitional function for fitness calculation has been introduced to accelerate the ability of the algorithm to find the optimal parameters for the ADRC controller. The tuned ADRC controller has been compared with the classical proportional-integral-derivative (PID) controller, with gust disturbances introduced to the UAV body axis. The results have shown that the tuned ADRC controller has faster response times and stronger disturbance rejection capabilities than the PID controller. Practical implications: The proposed CMP-BES algorithm, combined with a fitness function composed of transition functions, can be used to optimize the ADRC controller parameters for fixed-wing UAVs more quickly and effectively. The tuned ADRC controller has exhibited excellent robustness and disturbance rejection capabilities. Originality/value: The CMP-BES algorithm and transitional function have been proposed for the parameter optimization of the active disturbance rejection controller for fixed-wing UAVs. [ABSTRACT FROM AUTHOR]

Purpose: Loitering aerial vehicle (LAV) swarm safety flight control is an unmanned system control problem under multiple constraints, which are derived to prevent the LAVs from suffering risks inside and outside the swarms. The computational complexity of the safety flight control problem grows as the number of LAVs and of the constraints increases. Besides some important constraints, the swarms will encounter with sudden appearing risks in a hostile environment. The purpose of this study is to design a safety flight control algorithm for LAV swarm, which can timely respond to sudden appearing risks and reduce the computational burden. Design/methodology/approach: To address the problem, this paper proposes a distributed safety flight control algorithm that includes a trajectory planning stage using kinodynamic rapidly exploring random trees (KRRT*) and a tracking stage based on distributed model predictive control (DMPC). Findings: The proposed algorithm reduces the computational burden of the safety flight control problem and can fast find optimal flight trajectories for the LAVs in a swarm even there are multi-constraints and sudden appearing risks. Originality/value: The proposed algorithm did not handle the constraints synchronously, but first uses the KRRT* to handle some constraints, and then uses the DMPC to deal with the rest constraints. In addition, the proposed algorithm can effectively respond to sudden appearing risks by online re-plan the trajectories of LAVs within the swarm. [ABSTRACT FROM AUTHOR]

Purpose: Since the inception of aircraft, the phenomenon of spin has persistently accompanied aircraft, and research into spin has been ongoing. This paper aims to introduce an optimization technique to enhance the traditional geometric method for predicting steady spin, aiming to achieve more precise predictive outcomes. Design/methodology/approach: To begin with, the force and moment equations used for motion analysis are initially presented, followed by the establishment of the motion model. Subsequently, the forward problem is set up, and the equilibrium solutions for the left and right spins of the aircraft are determined using the geometric method under the basic and wingtip configurations, thus solving the forward problem. In the final stage, nonlinear inversion is applied, and the inversion objective function is formulated based on the least squares approach. Through iterative processes, the measured data are interpolated, leading to the acquisition of the accurate equilibrium solution. Findings: The findings indicate that the utilization of the nonlinear iterative inversion algorithm has effectively optimized the geometric method, yielding favorable outcomes. Postoptimization, the prediction accuracy has been enhanced, and the error has significantly diminished when compared to the preoptimization results. Originality/value: The nonlinear inversion algorithm is used to refine the steady spin prediction for general aviation aircraft. This approach significantly mitigates the precision issues inherent in the forward problem. As demonstrated through the simulations provided, the application of the nonlinear iterative algorithm to resolve the inversion function yields promising optimization outcomes. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to develop, extend and propose an improved proportional integral derivative (PID) rate control of a quadrotor unmanned aerial vehicle based on a convexity-based surrogated firefly algorithm. Design/methodology/approach: An improved PID controller structure is proposed for the rate dynamics of the quadrotor. Optimality of the controller is ensured by a recent, simple yet efficient firefly optimization method. The hybrid structure is further enhanced with a convexity-based surrogated model function. Findings: Monte Carlo, transient response, error metrics and histogram distribution analyzes are conducted to show the performance of the proposed controller. The performance of the proposed method is evaluated under various convex combination values to further investigate the effect of the proposed surrogated model. According to the results, the proposed method is capable of controlling the rate quadrotor dynamics with the steady-state error of 0.0023 (rad/s) for P, −0.0024 (rad/s) for Q and 0 (rad/s) for the R state, respectively. Also, the least mean objective value is achieved at = 0 value of convexity in Monte Carlo trials. Originality/value: The originality of this paper is to propose an improved PID rate controller with a convexity-based surrogated firefly algorithm. [ABSTRACT FROM AUTHOR]

Purpose: The use of aviation incident data to carry out aviation risk prediction is of great significance for improving the initiative of accident prevention and reducing the occurrence of accidents. Because of the nonlinearity and periodicity of incident data, it is challenging to achieve accurate predictions. Therefore, this paper aims to provide a new method for aviation risk prediction with high accuracy. Design/methodology/approach: This paper proposes a hybrid prediction model incorporating Prophet and long short-term memory (LSTM) network. The flight incident data are decomposed using Prophet to extract the feature components. Taking the decomposed time series as input, LSTM is employed for prediction and its output is used as the final prediction result. Findings: The data of Chinese civil aviation incidents from 2002 to 2021 are used for validation, and Prophet, LSTM and two other typical prediction models are selected for comparison. The experimental results demonstrate that the Prophet–LSTM model is more stable, with higher prediction accuracy and better applicability. Practical implications: This study can provide a new idea for aviation risk prediction and a scientific basis for aviation safety management. Originality/value: The innovation of this work comes from combining Prophet and LSTM to capture the periodic features and temporal dependencies of incidents, effectively improving prediction accuracy. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to present the idea of automatic flight control algorithms capable of performing an Immelmann turn manoeuvre automatically. This is a case of a manoeuvre far removed from so-called standard flight. The character of this manoeuvre and the range of changes in the aircraft flight parameters restrict the application of standard control algorithms. Furthermore, the possibility of acquiring full and detailed information about the aircraft's flight parameters is limited in such cases. This paper seeks to analyse an alternative solution that can be applied in some specific cases. Design/methodology/approach: This paper uses theoretical discussion and breakdowns to create the basics for development of structures of control algorithms. A simplified analytical approach was applied to tune regulators and the results of the research were verified in a series of software-in-the loop computer simulations. Findings: The structure of the control system enabling aerobatic flight (with the Immelmann turn as the selected example) was identified and the method for tuning the regulators is also presented. Practical implications: It could serve as a foundation for autopilots working in non-conventional flight states and aircraft automatic recovery systems. Originality/value: This paper presents the author's original approach to aircraft automatic control when high control precision is not the priority and not all flight parameters can be precisely measured. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to propose a high-precision attitude solution to solve the attitude drift problem caused by the dispersion of low-cost micro-electro-mechanical system devices in strap-down inertial navigation attitude solution of micro-quadrotor. Design/methodology/approach: In this study, a three-stage attitude estimation scheme that combines data preprocessing, gyro drifts prediction and enhanced unscented Kalman filtering (UKF) is proposed. By introducing a preprocessing model, the quaternion orientation is calculated as the composition of two algebraic quaternions, and the decoupling feature of the two quaternions makes the roll and pitch components independent of magnetic interference. A novel real-time based on differential value (DV) estimation algorithm is proposed for gyro drift. This novel solution prevents the impact of quartic characteristics and uses the iterative method to meet the requirement of real-time applications. A novel attitude determination algorithm, the pre-process DV-UKF algorithm, is proposed in combination with UKF based on the above solution and its characteristics. Findings: Compared to UKF, both simulation and experimental results demonstrate that the pre-process DV-UKF algorithm has higher reliability in attitude determination. The dynamic errors in the three directions of the attitude are below 2.0°, the static errors are all less than 0.2° and the absolute attitude errors tailored by average are about 47.98% compared to the UKF. Originality/value: This paper fulfils an identified need to achieve high-precision attitude estimation when using low-cost inertial devices in micro-quadrotor. The accuracy of the pre-process DV-UKF algorithm is superior to other products in the market. [ABSTRACT FROM AUTHOR]

Purpose: Owing to the complex space environment and limited computing resources, traditional and deep learning-based methods cannot complete the task of satellite component contour extraction effectively. To this end, this paper aims to propose a high-quality real-time contour extraction method based on lightweight space mobile platforms. Design/methodology/approach: A contour extraction method that combines two edge clues is proposed. First, Canny algorithm is improved to extract preliminary contours without inner edges from the depth images. Subsequently, a new type of edge pixel feature is designed based on surface normal. Finally, surface normal edges are extracted to supplement the integrity of the preliminary contours for contour extraction. Findings: Extensive experiments show that this method can achieve a performance comparable to that of deep learning-based methods and can achieve a 36.5 FPS running rate on mobile processors. In addition, it exhibits better robustness under complex scenes. Practical implications: The proposed method is expected to promote the deployment process of satellite component contour extraction tasks on lightweight space mobile platforms. Originality/value: A pixel feature for edge detection is designed and combined with the improved Canny algorithm to achieve satellite component contour extraction. This study provides a new research idea for contour extraction and instance segmentation research. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to introduce an artificial bee colony-based Kalman filter algorithm along with an extended objective function to ensure the optimality of the estimator of the quadrotor in the presence of unknown measurement noise statistics. Design/methodology/approach: Six degree-of-freedom mathematical model of the quadrotor is derived. Position controller for the quadrotor is designed. Kalman filter-based estimation algorithm is implemented in the sensor feedback loop. Artificial bee colony-based hybrid algorithm is used as an optimization method to handle the unknown noise statistics. Existing objective function is extended with a penalty term. Mathematical proof of the extended objective function is derived. Results of the proposed algorithm is compared with de facto genetic algorithm-based Kalman filter. Findings: Artificial bee colony algorithm-based Kalman filter and extended objective function duo are able to optimize the measurement noise covariance matrix with an absolute error as low as 0.001 [m2]. Proposed method and function is capable of reducing the noise from 2 to 0.09 [m] for x-axis, 3.4 to 0.14 [m] for y-axis and 3.7 to 0.2 [m] for z-axis, respectively. Originality/value: The motivation behind this paper is to bring a novel optimization-based solution for the estimation problem of the quadrotor when the measurement noise statistics are unknown along with an extended objective function to prevent the infeasible solutions with mathematical convergence analysis. [ABSTRACT FROM AUTHOR]

Purpose: The paper aims to present an idea of automatic control algorithms dedicated to both small manned and unmanned aircraft, capable to perform spin maneuver automatically. This is a case of maneuver far away from so-called standard flight. The character of this maneuver and the range of aircraft flight parameters changes restrict application of standard control algorithms. Possibility of acquisition full information about aircraft flight parameters is limited as well in such cases. This paper analyses an alternative solution that can be applied in some specific cases. Design/methodology/approach: The paper uses theoretical discussion and breakdowns to create basics for development of structures of control algorithms. Simplified analytical approach was applied to tune regulators. Results of research were verified in series of software-in-the loop, computer simulations. Findings: The structure of the control system enabling aerobatic flight (spin flight as example selected) was found and the method how to tune regulators was presented as well. Practical implications: It could be a fundament for autopilots working in non-conventional flight states and aircraft automatic recovery systems. Originality/value: The paper presents author's original approach to aircraft automatic control when high control precision is not the priority, and not all flight parameters can be precisely measured. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this research paper is to design a disturbance observer-based control based on the robust model reference adaptive backstepping sliding-mode control for attitude quadrotor model subject to uncertainties and disturbances. Design/methodology/approach: To estimate and reject the disturbance, a disturbance observer is designed for the exogenous disturbances with perturbation while a control criterion is developed for the tracking of desired output. To achieve the control performance, backstepping and sliding-mode control techniques are patched together to obtain robust chattering-free controller. Furthermore, a model reference adaptive control criterion is also combined with the design of robust control for the estimation and rejection of uncertainties and unmodeled dynamics of the attitude quadrotor. Findings: The findings of this research work includes the design of a disturbance observer-based control for uncertain attitude quadrotor system with the ability of achieving tracking control objective in the presence of nonlinear exogenous disturbance with and without perturbation. Practical implications: In practice, the quadrotor flight is opposed by different kinds of the disturbances. In addition, being an underactuated system, it is difficult to obtain an accurate mathematical model of quadrotor for the control design. Thus, a quadrotor model with uncertainties and disturbances is inevitable. Hence, it is necessary to design a control system with the ability to achieve the control objectives in the presence of uncertainties and disturbances. Originality/value: Designing the control methods for quadrotor control without uncertainties and disturbances is a common practice. However, investigating the uncertain quadrotor plant in the presence of nonlinear disturbances is rarely taken into consideration for the control design. Hence, this paper presents a control algorithm to address the issues of the uncertainties and disturbances as well as investigate a control algorithm to achieve tracking performance. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to establish an effective tracking algorithm for small unmanned aerial vehicles (UAVs) based on interacting multiple model (IMM) to take timely countermeasures against illegal flying UAVs. Design/methodology/approach: In this paper, based on the constant velocity model (CV), the maneuvering adaptive current statistical model (CS) and the angular velocity adaptive three-dimensional (3D) fixed center constant speed rate constant steering rate model, a small UAV tracking algorithm based on adaptive interacting multiple model (AIMM-UKF) is proposed. In addition, an adaptive robust filter is added to each model of the algorithm. The linear Kalman filter algorithm is attached to the CV model and the CS model and the unscented Kalman filter algorithm (UKF) is attached to the CSCDR model to solve the nonlinearity of the 3D turning model. Findings: Monte-Carlo simulation comparison with the other two IMM tracking algorithms shows that in the case of different movement modes and maneuvering strength of the UAV, the AIMM-UKF algorithm makes a good trade-off between the amount of calculation and filtering accuracy, which can maintain more accurate and stable tracking and has strong robustness. At the same time, after testing the actual observation data of the UAV, the results show that the AIMM-UKF algorithm state estimation trajectory can be regarded as an actual trajectory in practical engineering applications, which has good practical value. Originality/value: This paper presents a new small UAV tracking algorithm based on IMM and the advantages and practicability of this algorithm compared with existing algorithms are proved through experiments. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to introduce the theoretical basis of N-order spectral spreading-compressing (SSC) frequency shift interference algorithm and expand it to active cancellation. An active cancellation simulation and verification system based on N-order SSC algorithm is established and carried out; simultaneously, the absorbing material coating stealth simulation of two kinds of thickness is carried out to compare the stealth effect with active cancellation system. Design/methodology/approach: The active cancellation method based on N-order SSC algorithm is proposed based on theoretical formula derivation; the active cancellation simulation and verification system is established in MATLAB/Simulink. The full-size model is built by CATIA and meshed by hypermesh. The omnidirectional radar cross section (RCS) is calculated in cadFEKO, and the results are analyzed in postFEKO. Findings: The simulations are implemented on a stealth fighter, and results show that after active cancellation, the peak of spectrum analyzer has reduced in all azimuths, the omnidirectional RCS has also decreased and the detection probability of almost all azimuths has dropped under 50 per cent. The absorbing material coating stealth simulations of two kinds of thickness are carried out, and results show that the stealth effect of active cancellation is much better than absorbing material coating. Practical implications: An active cancellation system based on SSC algorithm is proposed in this paper, and the effect of active cancellation is verified and compared with that of absorbing materials. A new method for the current active stealth is provided in this paper. Originality/value: Active cancellation simulation and verification system is established. RCS calculation module, signal-to-noise-ratio (SNR) calculation module and detection probability module are built to verify the effect of active cancellation system. Simultaneously, the absorbing material coating stealth simulation is carried out, and the stealth effect of absorbing material coating and active cancellation are compared and analyzed. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to propose a new aerodynamic parameter estimation methodology based on neural network and output error method, while the output error method is improved based on particle swarm algorithm. Design/methodology/approach: Firstly, the algorithm approximates the dynamic characteristics of aircraft based on feedforward neural network. Neural network is trained by extreme learning machine, and the trained network can predict the aircraft response at (k + 1)th instant given the measured flight data at kth instant. Secondly, particle swarm optimization is used to enhance the convergence of Levenberg–Marquardt (LM) algorithm, and the improved LM method is used to substitute for the Gauss Newton algorithm in output error method. Finally, the trained neural network is combined with the improved output error method to estimate aerodynamic derivatives. Findings: Neither depending on the initial guess of the parameters to be estimated nor requiring numerical integration of the aircraft motion equation, the proposed algorithm can be used for unstable aircraft and is successfully applied to extract aerodynamic derivatives from both simulated and real flight data. Research limitations/implications: The proposed method requires iterative calculation and can only identify parameters offline. Practical implications: The proposed method is successfully applied to estimate aircraft aerodynamic parameters and can also be used as a new algorithm for other optimization problems. Originality/value: In this study, the output error method is improved to reduce the dependence on the initial value of parameters and expand its application scope. It is applied in aircraft aerodynamic parameter identification together with neural network. [ABSTRACT FROM AUTHOR]

Purpose |!|#8211; Unmanned aerial vehicles (UAVs) have a wide variety of applications such as surveillance and search. Many of these tasks are better executed by multiple UAVs acting as a group. One of the main problems to be tackled in a high-density UAV traffic scenario is that of collision avoidance among UAVs. The purpose of this paper is to give a collision avoidance algorithm to detect and resolve the conflicts of projected path among UAVs. Design/methodology/approach |!|#8211; The collision avoidance algorithm developed in the paper handles multiple UAV conflicts by considering only the most imminent predicted collision and doing a maneuver to increase the line-of-sight rate to avoid that conflict. After the collision avoidance maneuver, the UAVs fly to their destinations via Dubins shortest path to minimize time to reach destination. The algorithm is tested on realistic six degree of freedom UAV models augmented with proportional-integral controllers to hold altitude, velocity, and commanded bank angles. Findings |!|#8211; The paper shows, through extensive simulations, that the proposed collision avoidance algorithm gives a good performance in high-density UAV traffic scenarios. The proposed collision avoidance algorithm is simple to implement and is computationally efficient. Practical implications |!|#8211; The algorithm developed in this paper can be easily implemented on actual UAVs. Originality/value |!|#8211; There are only a few works in the literature that address multiple UAV collision avoidance in very high-density traffic situations. This paper addresses very high-density multiple UAV conflict resolution with realistic UAV models. [ABSTRACT FROM AUTHOR]

Purpose - Foreign object debris (FOD) poses a significant hazard to aviation safety and brings huge economic losses to the aerospace industry due to aircraft damage and out-of-service delays. Different schemes and sensors have been utilized for FOD detection. This paper aims to look into a video-based FOD detection system for airport runway security and propose a scheme for FOD surveillance network establishment. Design/methodology/approach - The FOD detection algorithm for the system is analyzed in detail, including four steps of pre-processing, background subtraction, post-processing and FOD location. Findings - The overall algorithm is applied to two sets of live video images. The results show that the algorithm is effective for FOD targets of different shades under different lighting conditions. The proposed system is also evaluated by the ground-truth data collected at Nanyang Airport. Practical implications - The runway security can be greatly increased by designing an affordable video-based FOD detection system. Originality/value - The paper presents critical techniques of video-based FOD detection system. The scheme for FOD surveillance network, as a significant part of aviation risk management at airports, is applicable and extensible. [ABSTRACT FROM AUTHOR]

Purpose - One of the primary problems in the field of on-orbit service and space conflict is related to the approach to the target. The development of guidance algorithms is one of the main research areas in this field. The objective of this paper is to address the guidance problem for autonomous proximity manoeuvres of a chase-spacecraft approaching a target spacecraft. Design/methodology/approach - The process of autonomous proximity is divided into three phases: proximity manoeuvre, fly-around manoeuvre, and final approach. The characteristics of the three phases are analyzed. Considering the time factor of autonomous proximity, different orbits for the three phases are planned. Different guidance algorithms, which are based on multi-pulse manoeuvres, are then devised. Findings - This paper proposes three phases of autonomous proximity and then designs a guidance method, which hinges on a multi-pulse algorithm and different orbits for the three phases; in addition, a method of impulse selection is devised. Practical implications - An easy methodology for the analysis and design of autonomous proximity manoeuvres is proposed, which could also be considered for other space applications such as formation flying deployment and reconfiguration. Originality/value - Based on this guidance method, the manoeuvre-flight period of the chase-spacecraft can be set in accordance with the mission requirements; the constraints on fuel mass and manoeuvre time are both considered and satisfied. Consequently, this proposed guidance method can effectively deal with the problem of proximity approach to a target spacecraft. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to propose an efficient algorithm for trajectory planning of unmanned aerial vehicles (UAVs) in 2D spaces. This paper has been motivated by the challenge to develop a fast trajectory planning algorithm for autonomous UAVs through mid-course waypoints (WPs). It is assumed that there is no prior knowledge of these WPs, and their configuration is computed as in-flight procedure. Design/methodology/approach – Since the off-line techniques cannot be applied, it is required to apply an online trajectory planning algorithm. For this reason, based on the optimal control and the geometry, each segment of trajectory is designed with respect to a local frame. The algorithm is implemented as a real-time manner in terms of the down-range variable. Findings – The proposed algorithm tries to find not only a feasible trajectory (the constraint includes the maximum heading angle rate) but also an optimal trajectory (the objective locally is to minimize the length of the path). This online trajectory planning algorithm gradually produces a smooth 2D trajectory aiming at reaching the mid-course WPs and the final target so that they are smoothly connected with each other. The mid-course WPs are described through the given down-range, cross-range, and heading angle. Originality/value – Based on geometrical principles, this algorithm is capable of re-planning the trajectory as in-flight manner, and the computational burden approaches the online capabilities for UAVs with high velocity. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to present the sample result of researches under original conception of the aircraft handling qualities evaluation scale. It allows rating and comparing of different control algorithms implemented into the control system in the simple way. Design/methodology/approach - The presented handling qualities evaluation scale takes into consideration two main elements to generate the grade of the tested control law. These are: pilot's workload during typical flight phases and the second is precision of control the pilot reaches controlling the plane. Findings - The paper presents possibilities of using of the proposed methodology. Also contributions of its use are described. Practical implications - The presented methodology can be applied to evaluate and compare handling qualities of different control algorithms supporting pilots. Originality/value - This paper presents original conception of handling qualities evaluation scale for aircraft equipped with fly-by-wire control system. [ABSTRACT FROM AUTHOR]

Purpose - To provide an autonomous navigation system to endow lunar rovers with increased autonomy both for exploration achievement of scientific goals and for safe navigation. Design/methodology/approach - First, algorithm and technique of initial position determination of lunar rovers are introduced. Then, matched-features set is build by multi steps of image processing such as feature detection, feature tracking and feature matching. Based on the analysis of the image processing error, a two-stage estimation algorithm is used to estimate the motion, robust linear motion estimation is executed to estimate the motion initially and to reject the outliers, and Levenberg-Marquardt non-linear estimation is used to estimate the motion precisely. Next, a weighted ZSSD algorithm is presented to estimate the image disparities by analyzing the traditional ZSSD. Finally, a virtual simulation system is constructed using the development tool of open inventor, this simulation system can provide stereo images for simulations of stereo vision and motion estimation techniques, simulation results are provided and future research work is addressed in the end. Findings - An autonomous navigation system is build based on stereo vision, the motion estimation algorithm and disparity estimation algorithm are developed. Research limitations/implications - The field test will be done in the near future to valid the autonomous navigation algorithm presented in this paper. Practical implications - A very useful source of information for graduate students and technical reference for researchers who work on lunar rovers. Originality/value - In this paper, stereo vision-based autonomous navigation techniques for lunar rovers are discussed, and an autonomous navigation scheme which based on stereo vision is presented, and the validity of all the algorithms involved is confirmed by simulations. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to justify the algorithm optimization based on a consideration of its accuracy characteristics in a pure coning motion, which is widely used in optimizing strapdown attitude algorithms to describe the special angular motion of a vehicle. Design/methodology/approach – Two more general angular motions of a vehicle were given: generalized vibration describing periodical motions and benign dynamic describing aperiodical motions. The algorithm performances were evaluated in these two motions. Findings – The theoretical analysis and numerical results show that errors of the algorithm optimized in pure coning motion are null or neglectable in these two motions, and performance of the optimized algorithm in a pure coning motion is superior to that of the non-optimized algorithm. Originality/value – The value of the paper lies in that the authors justify the concept optimizing strapdown attitude algorithms in a pure coning motion. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to present and demonstrate the efficiency of utilization of a new approach for estimating parameters of micromechanical gyros (MMG) during their operation. It is shown that the main sources of errors are due to the following three factors: measurement errors of micron deviations of the sensitive element, unknown actual value of difference between the frequencies of primary and secondary oscillations and unknown value of damping constant for the axis of secondary oscillations. The estimation of the last two factors during the operation leads to a significant increase of accuracy of MMG. The solution of the problem is presented in the current paper. Design/methodology/approach – To solve this problem, an original two-level algorithm intended for use in the embedded MMG controller is considered. The identification of the internal MMG parameters is carried out at the first stage. At the second stage, an MMG model is created, based on the results of identification of parameters at the first stage. This model is used as a basis for synthesis of a Kalman filter for estimating the angular velocity. The ways of simplifying identification algorithms and filtering for the purpose of their practical implementation are shown. Findings – This paper presents the research results on the effectiveness of the proposed algorithms. Results of simulation are used to confirm the effectiveness of the proposed algorithm in reducing the effect of changes in the design parameters of MMG on the accuracy of the angular velocity measurements. Practical implications – Proposed algorithms can be used in embedded MMG controllers. Originality/value – This paper presents a new approach for improving the accuracy of MMG by using a built-in algorithm for estimating parameters during system operation. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to innovatively propose to improve the efficiency of satellite observation and avoid the waste of satellite resources, a genetic algorithm with entropy operator (GAE) of synthetic aperture radar (SAR) satellites' task planning algorithm. Design/methodology/approach: The GAE abbreviated as GAE introduces the entropy value of each orbit task into the fitness calculation of the genetic algorithm, which makes the orbit with higher entropy value more likely to be selected and participate in the remaining process of the genetic algorithm. Findings: The simulation result shows that in a condition of the same calculate ability, 85% of the orbital revisit time is unchanged or decreased and 30% is significantly reduced by using the GAE compared with traditional task planning genetic algorithm, which indicates that the GAE can improve the efficiency of satellites' task planning. Originality/value: The GAE is an optimization of the traditional genetic algorithm. It combines entropy in thermodynamics with task planning problems. The algorithm considers the whole lifecycle of task planning and gets the desired results. It can greatly improve the efficiency of task planning in observation satellites and shorten the entire task execution time. Then, using the GAE to complete SAR satellites' task planning is of great significance in reducing satellite operating costs and emergency rescue, which brings certain economic and social benefits. [ABSTRACT FROM AUTHOR]

Purpose: Wind turbines are one of the best candidates to solve the problem of increasing energy demand in the world. The aim of this paper is to apply a multi-objective structural optimization study to a Phase II wind turbine blade produced by the National Renewable Energy Laboratory to obtain a more efficient small-scale wind turbine. Design/methodology/approach: To solve this structural optimization problem, a new Non-Dominated Sorting Genetic Algorithm (NSGA-II) was performed. In the optimization study, the objective function was on minimization of mass and cost of the blade, and design parameters were composite material type and spar cap layer number. Design constraints were deformation, strain, stress, natural frequency and failure criteria. ANSYS Composite PrepPost (ACP) module was used to model the composite materials of the blade. Moreover, fluid–structure interaction (FSI) model in ANSYS was used to carry out flow and structural analysis on the blade. Findings: As a result, a new original blade was designed using the multi-objective structural optimization study which has been adapted for aerodynamic optimization, the NSGA-II algorithm and FSI. The mass of three selected optimized blades using carbon composite decreased as much as 6.6%, 11.9% and 14.3%, respectively, while their costs increased by 23.1%, 29.9% and 38.3%. This multi-objective structural optimization-based study indicates that the composite configuration of the blade could be altered to reach the desired weight and cost for production. Originality/value: ACP module is a novel and advanced composite modeling technique. This study is a novel study to present the NSGA-II algorithm, which has been adapted for aerodynamic optimization, together with the FSI. Unlike other studies, complex composite layup, fiber directions and layer orientations were defined by using the ACP module, and the composite blade analyzed both aerodynamic pressure and structural design using ACP and FSI modules together. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to develop the governing differential equation and to analyze the free vibration of a rotating non-uniform beam having a flexible root and setting angle for variations in operating conditions and structural design parameters. Design/methodology/approach: Hamiltonian principle is used to derive the flapwise bending motion of the structure, and the governing differential equations are solved numerically by using differential quadrature with satisfactory accuracy and computation time. Findings: The results obtained by using the differential quadrature method (DQM) are compared to results of previous studies in the open literature to show the power of the used method. Important results affecting the dynamics characteristics of a rotating beam are tabulated and illustrated in concerned figures to show the effect of investigated design parameters and operating conditions. Originality/value: The principal novelty of this paper arises from the application of the DQM to a rotating non-uniform beam with flexible root and deriving new governing differential equation including various parameters such as rotary inertia, setting angle, taper ratios, root flexibility, hub radius and rotational speed. Also, the application of the used numerical method is expressed clearly step by step with the algorithm scheme. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to derive the output predictor for a stationary normal process with rational spectral density and linear stochastic discrete-time state-space model, respectively, as the output predictor is very important in model predictive control. The derivations are only dependent on matrix operations. Based on the output predictor, one quadratic programming problem is constructed to achieve the goal of subspace predictive control. Then an improved ellipsoid optimization algorithm is proposed to solve the optimal control input and the complexity analysis of this improved ellipsoid optimization algorithm is also given to complete the previous work. Finally, by the example of the helicopter, the efficiency of the proposed control strategy can be easily realized. Design/methodology/approach: First, a stationary normal process with rational spectral density and one stochastic discrete-time state-space model is described. Second, the output predictors for these two forms are derived, respectively, and the derivation processes are dependent on the Diophantine equation and some basic matrix operations. Third, after inserting these two output predictors into the cost function of predictive control, the control input can be solved by using the improved ellipsoid optimization algorithm and the complexity analysis corresponding to this improved ellipsoid optimization algorithm is also provided. Findings: Subspace predictive control can not only enable automatically tune the parameters in predictive control but also avoids many steps in classical linear Gaussian control. It means that subspace predictive control is independent of any prior knowledge of the controller. An improved ellipsoid optimization algorithm is used to solve the optimal control input and the complexity analysis of this algorithm is also given. Originality/value: To the best knowledge of the authors, this is the first attempt at deriving the output predictors for stationary normal processes with rational spectral density and one stochastic discrete-time state-space model. Then, the derivation processes are dependent on the Diophantine equation and some basic matrix operations. The complexity analysis corresponding to this improved ellipsoid optimization algorithm is analyzed. [ABSTRACT FROM AUTHOR]

Purpose -- This paper aims to develop and analyse a new multiple-hypothesis receiver autonomous integrity monitoring (RAIM) algorithm. The proposed algorithm can handle simultaneous multiple failures as well as a single failure. Design/methodology/approach -- The proposed algorithm uses measurement residuals and satellite observation matrices of several consecutive epochs for failure detection and exclusion. It detects failures by monitoring the error vector itself instead of monitoring the projection of the error vector. The algorithm reduces the minimum detectable bias via the relative receiver autonomous integrity monitoring (RRAIM) scheme. Findings -- The algorithm is able to detect any instance of multiple failures, including failures that are not detected by the conventional RAIM algorithm. It is able to detect multiple failures with magnitudes of several tens of meters, although the algorithm has to solve an ill-conditioning problem. The detection capability of the proposed algorithm is not dependent on satellite geometry. Research limitations/implications -- The algorithm assumes that the error vectors in three consecutive epochs have biases of similar magnitude. As a result, although the algorithm detects occurrences of drifting error, it cannot identify which measurement(s) has the critical error. Practical implications -- The paper includes implications for the development of the RAIM algorithm for aviation users. Especially, it can be a candidate for future standard architecture in multiple constellations, multiple frequency satellite-based augmentation system (SBAS) users. Originality/value -- The paper proposes a new multiple-hypothesis RAIM algorithm with an RRAIM concept. A detailed explanation of the algorithms, including rigorous mathematical expressions, is presented. The paper also includes an analysis of differences in detection capability between conventional algorithm and the proposed algorithm depending on satellite geometry. [ABSTRACT FROM AUTHOR]

Purpose: To guarantee the asymptotic stability of discrete-time nonlinear systems, this paper aims to propose an evolved bat algorithm fuzzy neural network (NN) controller algorithm. Design/methodology/approach: In evolved fuzzy NN modeling, the NN model and linear differential inclusion representation are established for the arbitrary nonlinear dynamics. The control problems of the Fisher equation and a temperature cooling fin for high-speed aerospace vehicles will be described and demonstrated. The signal auxiliary controlled system is represented for the nonlinear parabolic partial differential equation (PDE) systems and the criterion of stability is derived via the Lyapunov function in terms of linear matrix inequalities. Findings: This representation is constructed by sector nonlinearity, which converts the nonlinear model to a multiple rule base for the linear model and a new sufficient condition to guarantee the asymptotic stability. Originality/value: This study also injects high frequency as an auxiliary and the control performance to stabilize the nonlinear high-speed aerospace vehicle system. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to increase flight performance of small unmanned aerial vehicle (UAV) using simultaneous UAV and autopilot system design.Design/methodology/approach A small UAV is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory. Its wing and tail is able to move forward and backward in the nose-to-tail direction in prescribed interval. Autopilot parameters and assembly position of wing and tail to fuselage are simultaneously designed to maximize flight performance using a stochastic optimization method. Results are obtained are used for simulations.Findings Using simultaneous UAV and autopilot system design idea, flight performance is maximized.Research limitations/implications Permission of Directorate General of Civil Aviation in Turkey is required for testing UAVs in long range.Practical implications Simultaneous design idea is very beneficial for improving UAV flight performance.Originality/value Creating a novel method to improve flight performance of UAV and developing an algorithm performing simultaneous design idea. [ABSTRACT FROM AUTHOR]

Purpose |!|#8211; The purpose of this paper is to propose that the three-dimensional information of obstacles should be identified to allow unmanned aerial vehicles (UAVs) to detect and avoid obstacles existing in their flight path. Design/methodology/approach |!|#8211; First, the approximate outline of obstacles was detected using multi-scale-oriented patches (MOPS). At the same time, the spatial coordinates of feature points that exist in the internal outline of the obstacles were calculated through the scale-invariant feature transform (SIFT) algorithm. Finally, the results from MOPS and the results from the SIFT algorithm were merged to show the three-dimensional information of the obstacles. Findings |!|#8211; As the method proposed in this paper reconstructs only the approximate outline of obstacles, a quick calculation can be done. Moreover, as the outline information is combined through SIFT feature points, detailed three-dimensional information pertaining to the obstacles can be obtained. Practical implications |!|#8211; The proposed approach can be used efficiently in GPS-denied environments such as certain indoor environments. Originality/value |!|#8211; For the autonomous flight of small UAVs having a payload limit, this paper suggests a means of forming three-dimensional information about obstacles with images obtained from a monocular camera. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to use an ABC algorithm to improve the thrust–torque ratio of a rotating-wing unmanned aerial vehicle (UAV) model. Design/methodology/approach: The design of UAVs, such as aircraft, drones, helicopters, has become one of the popular engineering areas with the development of technology. This study aims to improve the value of thrust–torque ratio of an unmanned helicopter. For this purpose, an unmanned helicopter was built at the Faculty of Aeronautics and Astronautics, Erciyes University. The maximum thrust–torque ratio was calculated considering the blade length, blade chord width, blade mass density and blade twist angle. For calculation, artificial bee colony (ABC) algorithm was used. By using ABC algorithm, the maximum thrust–torque ratio was obtained against the optimum input values. For this purpose, a model with four inputs and a single output is formed. In the generated system model, optimum thrust–torque ratio was calculated by changing the input values used in the ±5% range. As a result of this study, approximately 31% improvement was achieved. According to these results, the proposed approach will provide convenience to the designers in the design of the rotating-wing UAV. Findings: According to these results, approximately 31% improvement was achieved, and the proposed approach will provide convenience to the designers in the design of the rotating-wing UAV. Research limitations/implications: It takes a long time to obtain the optimum thrust–torque ratio value through the ABC algorithm method. Practical implications: Using ABC algorithm provides to improve the value of thrust–torque ratio of an unmanned helicopter. With this algorithm, unmanned helicopter flies more than ever. Thus, the presented method based on the ABC algorithm is more efficient. Social implications: The application of the ABC algorithm method can be used effectively to calculate the thrust–torque ratio in UAV. Originality/value: Providing an original and penetrating a method that saves time and reduces the cost to improve the value of thrust–torque ratio of an unmanned helicopter. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to address the robust controller design problem for a class of fuzzy C-means clustering algorithm that is robust against both the plant parameter perturbations and controller gain variations. Based on Takagi–Sugeno (T-S) fuzzy model description, the stability and control problems of nonlinear systems are studied. Design/methodology/approach: A recently proposed integral inequality is selected based on the free-weight matrix, and the less conservative stability criterion is given in the form of linear matrix inequalities (LMIs). Findings: Under the premise that the controller and the system share the same, the method does not require the number of membership functions and rules. Practical implications: Furthermore, the modified controller in a large-scale nonlinear system is utilized as a stability criterion for a closed-loop T-S fuzzy system obtained by LMI, and is rearranged by a machine learning membership function. Originality/value: The closed-loop controller criterion is derived by energy functions to guarantee the stability of systems. Finally, an example is given to demonstrate the results. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to present a novel approach based on the differential search (DS) algorithm integrated with the adaptive network-based fuzzy inference system (ANFIS) for unmanned aerial vehicle (UAV) winglet design. Design/methodology/approach: The winglet design of UAV, which was produced at Faculty of Aeronautics and Astronautics in Erciyes University, was redesigned using artificial intelligence techniques. This approach proposed for winglet redesign is based on the integration of ANFIS into the DS algorithm. For this purpose, the cant angle (c), the twist angle (t) and taper ratio (λ) of winglet are selected as input parameters; the maximum value of lift/drag ratio (Emax) is selected as the output parameter for ANFIS. For the selected input and output parameters, the optimum ANFIS parameters are determined by the DS algorithm. Then the objective function based on optimum ANFIS structure is integrated with the DS algorithm. With this integration, the input parameters for the Emax value are obtained by the DS algorithm. That is, the DS algorithm is used to obtain both the optimization of the ANFIS structure and the necessary parameters for the winglet design. Thus, the UAV was reshaped and the maximum value of lift/drag ratio was calculated based on new design. Findings: Considerable improvements on the max E are obtained through winglet redesign on morphing UAVs with artificial intelligence techniques. Research limitations/implications: It takes a long time to obtain the optimum Emax value by the computational fluid dynamics method. Practical implications: Using artificial intelligence techniques saves time and reduces cost in maximizing Emax value. The simulation results showed that satisfactory Emax values were obtained, and an optimum winglet design was achieved. Thus, the presented method based on ANFIS and DS algorithm is faster and simpler. Social implications: The application of artificial intelligence methods could be used in designing more efficient aircrafts. Originality/value: The study provides a new and efficient method that saves time and reduces cost in redesigning UAV winglets. [ABSTRACT FROM AUTHOR]

Purpose - This paper seeks to examine the dynamic problem of associating measurements at a given period from several IR sensors in the presence of clutter, missed detections. Design/methodology/approach - On the basis of a dynamic S-D assignment algorithm, a new association algorithm for associating and tracking multiple targets is presented. By considering the special feature of the IR sensor, the dynamic assignment cost coefficient incorporates the radiation intensity information into the association process using a joint probabilistic model for the two separate sources of information (intensity and trajectory). Findings - The simulation results show that the new algorithm can attain almost the same accuracy of tracking estimation with less computational load by utilizing special feature information of the IR sensor into dynamic S-D assignment. Research limitations/implications - There are still some parameters to be set in advance, which influence the estimate result to some extent. And the tracking stage follows the image processor, so the tracking performance is also related with the quality of images. Those problems will be considered deeply in the future research based on different maneuvering level of targets and the real tracking environment. Practical implications - This new algorithm may be adopted by tracking systems based on passive sensors in the future. Originality/value - This new algorithm utilizes more information and fairly small and stable errors in position and velocity can be obtained. At the same time, it decreases computational load. [ABSTRACT FROM AUTHOR]

Purpose - This paper aims to investigate, a new optimization algorithm for complex orbit transfer missions with low-thrust propulsion system, which minimizes the drawbacks of traditional optimization methods, such as bad convergence, difficulty of initial guesses and local optimality. Design/methodology/approach - First, the trajectory optimization problem comes down to a nonlinear constraint parameter optimization by using the concept of traditional hybrid method. Then, one utilizes genetic algorithm (GA) to solve this parameter optimization problem after treating the constraints with the simulated annealing (SA) and random penalty function. Finally, one makes use of localized optimization to improve the precision of the final solutions. Findings - This algorithm not only keeps the advantages of traditional hybrid method such as high precision and smooth solutions, but also inherits the merits of GA which could avoid initial guess work and obtain a globally optimal solution. Research limitations/implications - Further, research is required to reduce the computational complexity when the transfer trajectory is very complex and/or has many adjustable variables. Practical implications - By using this method, the globally optimal solutions of some complex missions, which could not be obtained by traditional method, could be found. Originality/value - This method combines the GA with traditional hybrid method, and utilizes SA and random penalty functions to treat with constraints, and then gives out a super convergence way to find the globally optimal low-thrust transfer orbit. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to propose a constant-gain Kalman Filter algorithm based on the projection method and constant dimension projection, which ensures that the dimension of the observation matrix obtained is maintained when there is a satellite with multiple sensors.Design/methodology/approach First, a time-invariant observation matrix is determined with the projection method, which does not require the Jacobi matrix to be calculated. Second, the constant-gain matrix replaces the EKF (extended Kalman filter) gain matrix, which requires online computation, considerably improving the stability and real-time properties of the algorithm.Findings The simulation results indicate that compared to the EKF algorithm, the constant-gain Kalman filter algorithm has a considerably lower computational burden and improved real-time properties and stability without a significant loss of accuracy. The algorithm based on the constant dimension projection has better real-time properties, simpler computations and greater fault tolerance than the conventional EKF algorithm when handling an attitude determination system with three or more star trackers.Originality/value In satellite attitude determination systems, the constant-gain Kalman Filter algorithm based on the projection method reduces the large computational burden and improve the real-time properties of the EKF algorithm. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to improve the efficiency of particle optimization method by using direct and indirect surrogate modeling in inverse design problems.Design/methodology/approach The new algorithm emphasizes the use of a direct and an indirect design prediction based on local surrogate models in particle swarm optimization (PSO) algorithm. Local response surface approximations are constructed by using radial basis neural networks. The principal role of surrogate models is to answer the question of which individuals should be placed into the next swarm. Therefore, the main purpose of surrogate models is to predict new design points instead of estimating the objective function values. To demonstrate its merits, the new approach and six comparative algorithms were applied to two different test cases including surface fitting of a geographical terrain and an inverse design of a wing, the averaged best-individual fitness values of the algorithms were recorded for a fair comparison.Findings The new algorithm provides more than 60 per cent reduction in the required generations as compared with comparative algorithms.Research limitations/implications The comparative study was carried out only for two different test cases. It is possible to extend test cases for different problems.Practical implications The proposed algorithm can be applied to different inverse design problems.Originality/value The study presents extra ordinary application of double surrogate modeling usage in PSO for inverse design problems. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to evaluate the safety of formation flying satellites, and propose a method for practical collision monitoring and collision avoidance manoeuvre. Design/methodology/approach – A general formation description method based on relative orbital elements is proposed, and a collision probability calculation model is established. The formula for the minimum relative distance in the crosstrack plane is derived, and the influence of J2 perturbation on formation safety is analyzed. Subsequently, the optimal collision avoidance manoeuvre problem is solved using the framework of linear programming algorithms. Findings – The relative orbital elements are illustrative of formation description and are easy to use for perturbation analysis. The relative initial phase angle between the in-plane and cross-track plane motions has considerable effect on the formation safety. Simulations confirm the flexibility and effectiveness of the linear programming-based collision avoidance manoeuvre method. Practical implications – The proposed collision probability method can be applied in collision monitoring for the proximity operations of spacecraft. The presented minimum distance calculation formula in the cross-track plane can be used in safe configuration design. Additionally, the linear programming method is suitable for formation control, in which the initial and terminal states are provided. Originality/value – The relative orbital elements are used to calculate collision probability and analyze formation safety. The linear programming algorithms are extended for collision avoidance, an approach that is simple, effective, and more suitable for on-board implementation. [ABSTRACT FROM AUTHOR]

Purpose |!|#8211; The purpose of this paper is to present and validate an efficient time-marching free-vortex method for rotor wake analysis and study the rotor wake dynamics in transient and maneuvering flight conditions. Design/methodology/approach |!|#8211; The rotor wake is represented by vortex filament elements. The equations governing the convection, strain and viscous diffusion of the vortex elements are derived from incompressible Navier-Stokes equations based on the viscous splitting algorithm. The initial core size of the blade tip vortices is directly computed by a vortex sheet roll-up model. Then, a second-order time-marching algorithm is developed for solving the governing equations. The algorithm is formulated in explicit form to improve computing efficiency. To avoid the numerical instability, a high order variable artificial dissipative term is directly introduced into the algorithm. Finally, the developed method is applied to examine rotor wake geometries in steady-state and maneuvering flight conditions. Comparisons between predictions and experimental results are made for rotor wake geometries, induced inflow distributions and rotor transient responses, to help validate the new method. Findings |!|#8211; The algorithm is found to be numerically stable and efficient. The predicted rotor responses have good agreement with experimental data. The transient behavior of the wake dominates the rotor responses following rapid control inputs in hover. The wake curvature effect induced by rotor pitching or rolling rate significantly changes the rotor off-axis response. Research limitations/implications |!|#8211; This method should be further validated using experimental measurements of full-scale helicopter rotors. Originality/value |!|#8211; The paper presents a new time-marching free-vortex wake method, which is suitable for application in helicopter flight simulation. [ABSTRACT FROM AUTHOR]

Purpose - To design effective and practical controllers that use the adaptive fuzzy approaches and are applicable to helicopters. Design/methodology/approach - Based on Takagi-Sugeno fuzzy systems, a new direct adaptive fuzzy control scheme is developed for a class of nonlinear multiple-input-multiple-output systems. A simple observer is designed to generate an error signal for the adaptive law. The system states of the system are not required to be available for measurement. Findings - The overall adaptive scheme guarantees all the signals involved being uniformly bounded in the Lyapunov sense. Research limitations/implications - The implementation of this research work needs further investigation. Practical implications - The simplicity of the design algorithm facilitates the application of the design to helicopters by the use of Matlab. Originality/value - Experimental results of a two degree of freedom helicopter are presented to confirm the usefulness of the proposed new control scheme. [ABSTRACT FROM AUTHOR]

Purpose - This paper is concerned with an online parameter estimation algorithm for nonlinear uncertain time-varying systems for which no stochastic information is available. Design/methodology/approach - The estimation procedure, called nonlinear learning rate adaptation (NLRA), computes an individual adaptive learning rate for each parameter instead of using a single adaptive learning rate for all the parameters as done in stochastic approximation, each individual learning rate being controlled by a meta-learning rate rule for the sake of minimizing the measurement prediction error. The method does not require stochastic information about the system model and the measurement noise covariance matrices contrarily to the Kalman filtering. Numerical results about aircraft navigation trajectory tracking show that the method is able to estimate reliably time-varying parameters even in presence of measurement noise. Findings - The proposed algorithm is practically insensitive to changes in the meta-learning rate. Therefore, the performance of the method is stable with respect to the tuning parameter of the algorithm. Practical implications - The proposed NLRA method may be adopted for recursive parameter estimation of uncertain systems when no stochastic information is available. It may also be used for process regulation and dynamic system stabilization in feedback control applications. Originality/value - Provides a method for fast and practical computation of parameter estimates without requiring to know the model and measurement noise covariance matrices contrarily to existing stochastic estimation methods. [ABSTRACT FROM AUTHOR]

Purpose - This paper aims to present an algorithm for local mesh refinement of finite elements in a two-dimensional compressible fluid flow. Design/methodology/approach - The algorithm works on a principle of maximum gradient of fluid variables, e.g. pressure, velocity and density. The simulation of two-dimensional, transient, viscous, compressible, adiabatic flow of turbulent fluid through a De Laval nozzle was performed by the finite element method. The pressure gradient was used as a condition for mesh refinement. Findings - With the gradient method faster numerical calculations can be obtained. Boundary layer separation and locations of normal shock waves can be described on locally refined mesh. Research limitations/implications - Further development of the algorithm is required, especially the determination of the gradient criterion. Originality/value - The paper provides a new approach to mesh refinement. The mesh is refined automatically. Calculation time and required computer memory are decreased. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to propose, as the first time, the interval type-2 adaptive network-fuzzy inference system (ANFIS) structure, which is given better results compared to previously presented in the open literature. So, the ANFIS can be used effectively for training of interval type-2 fuzzy logic system (IT2FLS) parameters. Design/methodology/approach: Karnik–Mendel algorithm (KMA) is modified to use in interval type-2 ANFIS. The modified Karnik–Mendel algorithm (M-KMA) is implemented to change the uncertain ANFIS parameters into known ones. In this way, the interval type-2 ANFIS removes uncertainties of IT2FLS. Therefore, the interval type-2 ANFIS is reduced to a simple one, i.e. less mathematical operation required. Only consequent parameters are trained, and the consequent parameters are chosen in the form of crisp. Findings: By applying the mentioned procedure, it can be shown that interval type-2 ANFIS has generally better results compared to type-1 ANFIS. However, it was noticed that the worst results obtained in the case of interval type-2 ANFIS are equal to the best result obtained in the case of type-1 ANFIS. Therefore, users in this field can use this approach in solving nonlinear problems. Practical implications: The interval type-2 ANFIS can be used as controller for highly nonlinear systems such as air vehicles. Originality/value: As stated in the open literature, it is ineffective to use ANFIS for IT2FLS. In this study, the KMA is modified for IT2FLS, and it is seen that the ANFIS can be used effectively for IT2FLS. [ABSTRACT FROM AUTHOR]

Purpose Conceptual and preliminary aircraft concepts are getting mature earlier in the design process, than ever before. To achieve that advanced level of maturity, multiple multidisciplinary analyses have to be done, often with usage of numerical optimization algorithms. This calls for right tools that can handle such a demanding task. Often the toughest part of a modern design is handling an aircraft’s computational models used for different analysis. Transferring geometry and loads from one program to another, or modifying internal structure, takes time and is not productive. Authors defined the concept of a common computational model (CCM), which couples programs from different aerospace scientific disciplines. Data exchange between the software components is compatible, and multidisciplinary analysis can be automated to high degree, including numerical optimization.Design/methodology/approach The panel method was applied to aerodynamic analysis and was coupled with open-source FEM code within one computational process.Findings The numerical results proved the effectiveness of developed methodology.Practical implications Developed software can be used within the design process of a new aircraft.Originality/value This paper presents an original approach for advanced numerical analysis, as well as for multidisciplinary optimization of an aircraft. The presented results show possible applications. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to document an efficient and accurate approach to generate aerodynamic tables using computational fluid dynamics. This is demonstrated in the context of a concept transport aircraft model.Design/methodology/approach Two designs of experiment algorithms in combination with surrogate modelling are investigated. An adaptive algorithm is compared to an industry-standard algorithm used as a benchmark. Numerical experiments are obtained solving the Reynolds-averaged Navier–Stokes equations on a large computational grid.Findings This study demonstrates that a surrogate model built upon an adaptive design of experiments strategy achieves a higher prediction capability than that built upon a traditional strategy. This is quantified in terms of the sum of the squared error between the surrogate model predictions and the computational fluid dynamics results. The error metric is reduced by about one order of magnitude compared to the traditional approach.Practical implications This work lays the ground to obtain more realistic aerodynamic predictions earlier in the aircraft design process at manageable costs, improving the design solution and reducing risks. This may be equally applied in the analysis of other complex and non-linear engineering phenomena.Originality/value This work explores the potential benefits of an adaptive design of experiment algorithm within a prototype working environment, whereby the maximum number of experiments is limited and a large parameter space is investigated. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to present a multiple-model adaptive estimator (MMAE) to calibrate the star sensor low frequency error (LFE). The star sensor LFE, which is caused primarily by the periodic thermal distortion, has a great impact on spacecraft attitude determination accuracy.Design/methodology/approach The unfavorable effect of the LFE can be partly eliminated by using the calibration algorithm based on the augmented Kalman filter (AKF). However, the AKF may be worse than the traditional Kalman filter (KF) in the absence of the LFE. To cope with this problem, the MMAE is applied first time for combining the AKF and the KF in the spacecraft attitude determination system, such that satisfactory performance can be achieved in different operating scenarios.Findings The convergence of the presented MMAE is demonstrated through a formal derivation. A novel method is proposed to tune the MMAE design parameter, such that the convergence rate of the estimator is increased. It is shown via numerical studies that the presented algorithm outperforms the AKF and the KF.Practical implications The calibration algorithm is applicable for spacecraft attitude determination.Originality/value An effective star sensor LFE calibration algorithm based on the MMAE is developed. In addition, a novel method is proposed to increase convergence rate of the estimator. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to get the topology shape and material distribution of composite rotor beam under the requirement of cross-sectional characteristics. Design/methodology/approach – A new multi-material topology optimization method is given. Designated shear center (SC) position and stiffness terms are combined as the objective function. Multi-material model including isotropic and anisotropic materials are employed. Sensitivity analysis is given based on gradient-based algorithm, and density filtering scheme is adopted to avoid checkerboard problem. Findings – The topology design method of composite rotor beam provides innovative cross-sectional shape and material distribution method. The final topology shape like “ > ” is given for different material types and cross-sectional shape under SC position requirement. The coefficient of stiffness components has great influence on the cross-sectional final topology shape. Research limitations/implications – The proposed method is just to give cross-sectional topology shape. To obtain final actual composite rotor beam structure, shape and size optimization should be conducted if the topology shape is given. Practical implications – This method is suitable for the preliminary design of helicopter rotor beam to get designated SC position and stiffness terms. Originality/value – The proposed method provides a new gradient-based algorithm for multi-material topology optimization design of composite rotor beam. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to develop a multiobjective differential evolution (MODE)-based extended H-infinity controller for autonomous helicopter control. Design/methodology/approach – Development of a MATLAB-based MODE suitable for controller synthesis. Formulate the H-infinity control scheme as an extended H-infinity loop shaping design procedure (H∞-LSDP) with incorporation of v-gap metric for robustness to parametric variation. Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance. Findings – The proposed optimized H-infinity control was able to yield set of Pareto-controller candidates with optimal compromise between conflicting stability and time-domain performances required in autonomous helicopter deployment. The result of performance evaluation shows robustness to parameter variation of up to 20 per cent variation in nominal values, and in addition provides satisfactory disturbance rejection to wind disturbance in all the three axes. Research limitations/implications – The formulated H-infinity controller is limited to hovering and low speed flight envelope. The optimization is focused on weighting function parameters for a given fixed weighting function structure. This thus requires a priori selection of weighting structures. Practical implications – The proposed MODE-infinity controller algorithm is expected to ease the design and deployment of the robust controller in autonomous helicopter application especially for practicing engineer with little experience in advance control parameters tuning. Also, it is expected to reduce the design cycle involved in autonomous helicopter development. In addition, the synthesized robust controller will provide effective hovering/low speed autonomous helicopter flight control required in many civilian unmanned aerial vehicle (UAV) applications. Social implications – The research will facilitate the deployment of low-cost, small-scale autonomous helicopter in various civilian applications. Originality/value – The research addresses the challenges involved in selection of weighting function parameters for H-infinity control synthesis to satisfy conflicting stability and time-domain objectives. The problem of population initialization and objectives function computation in the conventional MODE algorithm are addressed to ensure suitability of the optimization algorithm in the formulated H-infinity controller synthesis. [ABSTRACT FROM AUTHOR]

Purpose – The aim of this paper is to propose a new coning correction algorithm, based on the singular perturbation technique, for the attitude update computation with non-ideal angular rate information. Design/methodology/approach – Unlike conventional coning correction algorithms, the new method uses angular rate two-time scale model to construct the coning correction term of attitude update. In order to achieve balanced real/pseudo coning correction performance, the selection guidelines of the new algorithm parameters are established. Findings – Performance of the new algorithm is evaluated by comparison with the conventional algorithm in no ideal sensors undergoing stochastic coning environments. The accuracy of attitude update can be improved effectively with reduced computational workload by using this new coning algorithm as compared with conventional ones. Practical implications – The proposed coning correction algorithm can be implemented with angular rate sensors in UAV (unmanned aerial vehicle) and other aircrafts attitude estimation for navigation and control applications. Originality/value – Singular perturbation is an effective method for structuring coning correction algorithm with filtered angular rate outputs in stochastic coning environments. The improved coning correction algorithm based on singular perturbations reduces the real and pseudo coning effects effectively as compared with conventional ones. It is proved to be valid for improvement of accuracy with reduced computations of the attitude update. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to propose a new algorithm for pendulum-like oscillation control of an unmanned rotorcraft (UR) in a reconnaissance mission and improve the stabilizing performance of the UR's hover and stare. Design/methodology/approach – The algorithm is based on linear-quadratic regulator (LQR), of which the determinable parameters are optimized by the artificial bee colony (ABC) algorithm, a newly developed algorithm inspired by swarm intelligence and motivated by the intelligent behaviour of honey bees. Findings – The proposed algorithm is tested in a UR simulation environment and achieves stabilization of the pendulum oscillation in less than 4s. Research limitations/implications – The presented algorithm and design strategy can be extended for other types of complex control missions where relative parameters must be optimized to get a better control performance. Practical implications – The ABC optimized control system developed can be easily applied to practice and can safely stabilize the UR during hover and stare, which will considerably improve the stability of the UR and lead to better reconnaissance performance. Originality/value – This research presents a new algorithm to control the pendulum-like oscillation of URs, whose performance of hover and stare is a key issue when carrying out new challenging reconnaissance missions in urban warfare. Simulation results show that the presented algorithm performs better than traditional methods and the design process is simpler and easier. [ABSTRACT FROM AUTHOR]