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Failures of the aircraft control system sensors can cause both deterioration of stability and controllability characteristics and the inability of safe automatic control. It is necessary to detect and isolate such failures to determine the time and place of their occurrence in order to disable failed sensors or to diagnose them subsequently for reconfiguration during the flight. The direct use of traditional parametric approaches for sensors health monitoring by using their mathematical models is impossible due to the lack of data about the true information input signals received by their sensitive elements. This leads to the necessity of solving the problem of modeling the aircraft flight dynamics with a high level of uncertainties, which makes it difficult to utilize the functional control methods and necessitate the use of excessive sensor hardware redundancy. Well-known nonparametric methods either require a priori knowledge base, preliminary training or long-term tuning on a large volume of real flight data or have low selective sensitivity for reliable detection of failed sensors. In this work, the original nonparametric criterion for detecting and isolating sensors failures is derived. Its sensitivity is analyzed by using a complete nonlinear mathematical model of aircraft flight dynamics with a regular flight control system. The theoretical value and the criterion sensitivity coefficients are determined. The formula for the automatic evaluation of the float criterion threshold value is given. A high convergence of the results with theoretical ones is shown. This makes it possible to use the obtained criterion not only for the instant detection and isolation of sensors failures, but also for preliminary diagnostics of their quantitative characteristics.

The INS/GNSS integration is the commonly used technique for hypersonic vehicle navigation. However, owing to the complicated flight dynamics with high maneuverability and large flight envelope, the dynamic model of INS/GNSS integration inevitably exists errors which degrades the navigation performance of a hypersonic vehicle seriously. In this paper, a new model predictive based unscented Kalman filter (MP-UKF) is proposed to address this problem. The MP-UKF employs the concept of model predictive filter for the establishment of a dynamic model error estimator, and it subsequently compensate the model error estimation to UKF for nonlinear state estimation. Since the MP-UKF could predict the dynamic model error persistently and correct the filtering procedure of UKF online, it improves the UKF adaptiveness and is promising for the performance enhancement of INS/GNSS integration for hypersonic vehicle navigation. Simulation results and comparison analysis have been conducted to demonstrate the effectiveness of the proposed method.

The cause of the rapid growth and enhancement in the dynamics of unmanned aerial vehicles (UAVs) is due to its vast utilization in every-day application. The major advantage of UAVs is no risk of human life with secure and suitable surveillance. The UAV facilitates in live video streaming and wide aerial coverage for monitoring. In this project, a type of UAV named quadcopter has been developed. The work mainly consists of design of the quadcopter frame, interfacing of the brushless DC motors and bluetooth module with the microcontroller, and adjustment of the roll, pitch, and yaw for keeping the smooth flight dynamics by flight controller board containing MEMS sensors, i.e., gyroscope, accelerometer, magnetometer, and pressure sensors. The repeated simulation and testing has been carried out in MATLAB for the mathematical modeling of the dynamics of the system, i.e., Euler method for solving differential equation for finding system states, computation of the rotation matrix R and functions to convert from an angular velocity vector w to the derivatives of roll, pitch, and yaw. The improvement in the parameters of the flight dynamics and removing the errors to gain stability in the frame are the main core issues which have been achieved by the several iterations. A closed-loop control system, i.e., PID controller, has been simulated and carefully designed for stabilizing the actual angle from the sensors and desired angle from the pilot. The reduced error rate of 0.05 degrees after every 10 s was achieved.

This paper presents the technique to implement stability and control of multirotor unmanned aerial vehicle (UAV). The output of the inertial sensors like accelerometer and gyroscope is noisy. These sensors are used to get the orientation and attitude of the UAV. Most of the flight controllers available these days are built to fly in a very specific environment. One cannot fly with these flight controllers in heavy wind or where precise control is required. As a result, the UAV’s that use these flight controllers feel unresponsive and sloppy. The goal here is to get excellent flight dynamics and robust flight control which can fly in any conditions. The UAV’s should be able to do aggressive maneuvering, fault tolerance etc. In the proposed design, Kalman Filter algorithm is implemented to get precise values from Inertial Measurement Unit. Extended Kalman Filter (EKF) is used for sensor fusion and to get precise values from Inertial Measurement Unit PID algorithms are used to stabilize the UAV and for maneuver Rotational speed of the four motors can be increased or decreased independently to correct the orientation or position. The flight controller is built with STM32F4 ARM controller.

High quality simulation environment can accelerate the development of the control software. Also, it is a good tool for the beginner to study how the control software works. The goal of this paper is aiming at designing a real time HIL experimental platform for quadrotor autopilot software design, validation and optimization. The platform is mainly composed of four blocks: A quadrotor dynamics model, a flight control system, a communication agent and hardware devices for control input and output. The flight dynamics model of a quadrotor build in this paper is to simulate the physics involved with its movement. It receives input signals from the autopilot controller, and returns the quadrotor’s real time pose, position, velocities, and etc. resulting from the input signals to the autopilot controller. A communication agent implements bidirectional communication between the flight dynamics model and the autopilot controller. Hardware devices for input and output is used to change the flight mode, indicate the flight state and test the control law. This paper focuses primarily on developing an experiment platform that works for control software validation. It allows for the safe testing of experimental code and settings, especially for aggressive and agile flight test.

TZ-1 satellite is the first Software Define Satellite, which is developed by Shanghai Engineering Center for Microsatellites and intends to validate software define technology in orbit. TZ-1 satellite is a typical low-cost satellite and equipped with the attitude control components, including sun sensors, magnetometers, magnetic torquers and a momentum wheel. Based on these low-cost attitude control components, a high-reliable attitude control scheme is proposed and the well-designed algorithms provide a good attitude pointing accuracy and proper stability for the satellite, which make the implements of the relative experiments possible. ADCS (Attitude determine and control system) simulations show that the designed rate damping algorithm for large angular velocity cases could de-tumble the satellite perfectly, even if the initial angular velocity is up to 70 deg/s. The sun pointing algorithm is robust and sun angle is always lower than 20 degrees. The nadir pointing algorithm is perfect and the satellite pointing accuracy and stability have been well guaranteed. According to the telemetry data, attitude control system works well, attitude curve changes are consistent with the simulations, and the satellite pointing accuracy and stability are the same with expectations. Attitude control system of TZ-1 components is a low-cost but robust one, which could be used for reference by the following low-cost LEO satellites.

In order to realize the rapid verification of the control algorithm of the tilt tri-rotor UAV, this paper presents the design and implementation of the SIL(software in the loop) simulation system using X-plane software. Firstly, According to the actual parameters of the designed tilt tri-rotor UAV, a full scale digital model that can simulate actual flight dynamics is designed by Plane Maker. Secondly, the flight control scheme consists of mode transition strategy, hybrid controller and control allocation is illustrated and carried out using Matlab/Simulink. Then, using UDP protocol, the UAV model based on X-Plane and the controller based on MATLAB / Simulink are combined to form the SIL simulation system. Finally, the flight simulations are finished using the SIL system, and the results show that the designed simulation system is suitable for the verification of the flight control algorithm of the tilt tri rotor UAV.

In the paper, the problem of minimum-fuel aeroassisted spacecraft regional reconnaissance (orbital hopping) is considered. A new nonlinear constrained optimal control formulation is designed and constructed so as to describe this mission scenario. This formulation contains multiple exo-atmospheric and atmospheric flight phases and correspondingly, two sets of flight dynamics. The constructed continuous-time optimal control system is then discretized via a multi-phase global collocation technique. The resulting discrete-time system is optimized using a newly proposed gradient-based optimization algorithm. Several comparative simulations are carried out and the obtained optimal results indicate that it is effective and feasible to use the proposed multi-phase optimal control design for achieving the aeroassisted vehicle orbital hopping mission.

Attitude Determination and Control Subsystem (ADCS) in spacecraft is one of the vital systems for low-earth-orbit spacecraft in which the pointing accuracy is a highly recommended factor to satisfy its mission requirements. When any malfunction takes place at attitude actuator, the spacecraft will not satisfy the required mission objectives. It is required to identify specific faults for attitude actuators in a manner that helps to optimally recover this type of anomaly. An efficient anomaly detection and identification technique is a suitable way to identify such anomaly. This research introduces an accurate and high-performance methodology for fault detection and identification for spacecraft reaction wheels (RW) as (ADCS) actuator. Proposed approach is to differentiate among signatures of possible anomalies that may be occurred at RW like under-voltage, over-voltage, current losses, temperature decrease, and temperature increase. “Prony method,” as a feature extraction technique, is used to discriminate between normal system behavior and anomalies based on the three-axis spacecraft RW operation. A feed-forward neural network with back-propagation algorithm is used for anomaly identification. Prony order assessment is also carried out to obtain the proper order of poles and zeros to minimize the processing time required for identification. The results verify that the proposed anomaly identification is successfully accomplished with high degree of confidence and with minimal execution time. Research approach leads to generic methodology for anomaly identification process among all spacecraft subsystem anomalies.

A combination of vibrational inputs and state feedback is applied to control the flight of a biomimetic air vehicle. First, a control strategy is developed for longitudinal flight, using a quasi-steady aerodynamic model and neglecting wing inertial effects. Vertical and forward motion is controlled by modulating the wings’ stroke and feather angles, respectively. Stabilizing control parameter values are determined using the time-averaged dynamic model. Simulations of a system resembling a hawkmoth show that the proposed controller can overcome modeling error associated with the wing inertia and small parameter uncertainties when following a prescribed trajectory. After introducing the approach through an application to longitudinal flight, the control strategy is extended to address flight in three-dimensional space.

This paper presents methodology to determine dynamic models and the suitable controllers for FY450 Firefly quadcopter. Frequency response system identification technique via software package Comprehensive Identification from Frequency Response (CIFER) was applied in this research. Pixhawk hardware with PX4 Flight stack firmware was implemented as a flight controller. The measurement of inputs and outputs during hovering flight maneuver with frequency sweep input was utilized to determine the unknown parameters of SISO mathematical model. Then after mathematical models were identified, the dynamic models of roll, pitch and yaw response respectively were employed to tuning the gains of PX4 controller structure with globally offline optimization technique. With this presented method, satisfied flight dynamics meets the desired performances without the requirement of numerous in-flight tuning.

Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.

A closed-loop fault detection problem is investigated for the full-envelope flight vehicle with measurement delays, where the flight dynamics are modeled as a switched system with delayed feedback signals. The mode-dependent observer-based fault detection filters and state estimation feedback controllers are derived by considering the delays’ impact on the control system and fault detection system simultaneously. Then, considering updating lags of the controllers/filters’ switching signals which are introduced by the delayed measurement of altitude and Mach number, an asynchronous H ∞ analysis method is proposed and the system model is further augmented to be an asynchronously switched time-delay system. Also, the global stability and desired performance of the augmented system are guaranteed by combining the switched delay-dependent Lyapunov–Krasovskii functional method with the average dwell time method (ADT), and the delay-dependent existing conditions for the controllers and fault detection filters are obtained in the form of the linear matrix inequalities (LMIs). Finally, numerical example based on the hypersonic vehicles and highly maneuverable technology (HiMAT) vehicle is given to demonstrate the merits of the proposed method.

The problem of the unmanned flight vehicle moving along the given route in a perturbed environment comes down to that of pursuing a target which simulates motion of the reference flight vehicle in compliance with its task. A scheme was proposed of a control system selecting the control strategy according to the current states of the flight vehicle and target. Consideration was given to the issues of the lead determination of the point of meeting of the flight vehicle with the target and rearrangement in the transfer functions of the equations of longitudinal and lateral motions of the flight vehicle in a restless tmosphere. The systems of automatic stabilization of the pitch and yaw angles with autopilot are used as the internal control loops. In the experimental part of the paper, the FV motion is modeled under the control constraints.

This paper describes a model preditictive control scheme for the horizontal flight guidance of an unmanned powered paraglider (PPG). These aircraft are characterized by their comparatively high wind-to-airspeed ratio and slow, nonlinear flight dynamics. The proposed control scheme consists of two cascaded loops: The inner loop is the heading controller, which is implemented using conventional feedback control; the outer loop controls the horizontal flight path and is implemented using a model predictive controller. Due to the high wind-to-airspeed ratio, wind needs to be taken into account during prediction. To this end, we adopt a simple and robust wind estimation, based only on inertial velocities and heading information. To solve the computationally demanding nonlinear, constrained optimization problem we use a domain-specific heuristic enabling the implementation on a microcontroller. The control scheme is validated using simulations and flight tests, demonstrating good, reproducible flight path following capabilities.

This paper investigates the closed-loop fault detection problem for networked flight control system with asynchronous switching. Firstly, the original flight dynamics is modelled as a linear switched system including multiple operating points. Secondly, observer-based fault detection filters and robust tracking controllers are designed synergistically to detect faults and make the system track a given command signal. Then, an asynchronous H ∞ analytical method was proposed to overcome the asynchronous phenomenon between the filters/controllers and flight dynamics which is caused by the updating intervals of the system states. Moreover, the globally uniformly asymptotically stability in the mean (GUAS-M) are guaranteed by combing the Lyapunov function method with average dwell time (ADT) method.

This research investigation looks at an intelligent reconfigurable control methodology that is used for the design and implementation of control system for commercial aircrafts operating under known and unknown flight conditions. The intelligent reconfigurable methodology is based upon adaptive neuro fuzzy inference system (ANFIS) and is used to integrate the actions of multiple adaptive controllers designed and implemented following the model reference control strategy and architecture. A transport control model (TCM) of commercial aircrafts is used to generate linearized models of its flight dynamics and then the models are utilized in the development and determining the effectiveness of the developed intelligent reconfigurable control system. This methodology attempts to provide a solution for the problems in using an indicator function as presented in previous works. The proposed intelligent reconfigurable control system is developed in two phases: first, a set of flight reference models are established and associate set of adaptive controllers are designed. Second, the ANFIS system is developed for the elevator flight surfaces and trained based on the performance of two designed adaptive controllers using two specific operating conditions to maintain and adjust the angle of attack (AOA) of commercial aircrafts. The testing of the ANFIS system used aircraft dynamic operating under condition that wasn't used in the design of the adaptive controllers. The results showed the intelligent reconfigurable ANFIS control system was able to achieve the desired result of combining the actions of two adaptive controllers for aircraft operating under an unknown operating condition.

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

In this paper, the dynamical simulation of a nonlinear aircraft rotor system in Herbst maneuvering flight is carried out, though which the load control is discussed for safety purposes. The equations of motion of the system are set up by using Lagrange’s equation, in which, the effects of maneuvering flight are formulated by the flight parameters of the aircraft. By employing the method of closest unstable equilibrium point, the stability of periodic solutions for the primary resonance of the system in steady flight is analyzed to demonstrate the existence of double steady solutions in some rotation speed region near the critical speed and the possibility of the switch of them due to the effect of maneuvering flight. By introducing the Herbst flight parameters from the results of a relative control simulation, the dynamical simulation of the system is carried out, from which the switch of the smaller solution of amplitude to the larger solution is observed. Furthermore, the load control is designed by adding a gain λ to the Herbst flight parameters to avoid the switch. Through numerical experiments, it is found that λ = 0.679 is the critical condition of the switch. The results in this paper will provide a better understanding for the effect of aircraft maneuvering flight on the dynamics of the rotor system.

The versatile and smart feature of MPC is the ease that it can work with MIMO plants, whereas adaptive PID controller is very difficult to implement and also provides unsatisfactory results unless updated to a rather complex controller by incorporating intelligent algorithms such as Particle Swarm Optimization, Genetic Algorithm and Neural Network. In this paper we present a novel but simple Model Predicative Controller for the Flight Control of Ornithopters. The performance was evaluated for the MISO and MIMO setup for almost all possible cases of various operating conditions resulting not only in faster response but also eliminating overshoot. The results obtained from the use of Model Predictive Controller for the flight control of the Micro Arial Vehicles shows comprehensively that MPC can be used as the future means for the control of these sophisticated and very complex ornithopters.

This paper proposes an adaptive augmentation control design approach of the gain-scheduled controller. This extension is motivated by the need for augmentation of the baseline gain-scheduled controller. The proposed approach can be utilized to design flight control systems for advanced aerospace vehicles with a large parameter variation. The flight dynamics within the flight envelope is described by a switched nonlinear system, which is essentially a switched polytopic system with uncertainties. The flight control system consists of a baseline gain-scheduled controller and a model reference adaptive augmentation controller, while the latter can recover the nominal performance of the gain-scheduled controlled system under large uncertainties. By the multiple Lyapunov functions method, it is proved that the switched nonlinear system is uniformly ultimately bounded. To validate the effectiveness of the proposed approach, this approach is applied to a generic hypersonic vehicle, and the simulation results show that the system output tracks the command signal well even when large uncertainties exist.

The vehicle is expected to impact the target with high precision of position and direction while all the constraints are satisfied. First an optimal control model for terminal flight dynamics is formulated and the multi-shooting method is employed to obtain numerical optimal solutions. Based on the optimal solutions, a practical flight strategy is proposed to design the terminal guidance law. The guidance law is on the basis of a proportional navigation (PN) form and the resulting PN parameters are seriously selected to mimic the proposed flight strategy. To enhance the guidance performance, an on-line correction algorithm of guidance parameters is devised to eliminate the adverse effect caused by the lag-free assumption and a critical parameter for entry strategy is designed to guarantee the trajectory convergence. Simulation results show that a high precision terminal impact can be achieved and the trajectory is consistent with the optimization results.

The purpose of this work is to design a new layout for a quadrotor unmanned aerial vehicle (UAV) for experimental customized control-system validation. Geometrical and structural properties have been computed, and commercial off-the-shelf equipment has been selected. The flight control system, both hardware and software, has been custom developed; the same applies for the mathematical model describing the flight dynamics. Two proportional-derivative (PD) controllers have been designed and experimentally tested. A different control strategy with a state feedback controller has been implemented, assigning a robust eigenstructure and the desired dynamic specifications. An adaptive algorithm, which guarantees a uniformly bounded response for both the inputs and the outputs, has been presented. An L1 adaptive controller has been studied and implemented, including the state predictor and the adaptive and control laws. Tests with the PD controller have shown slowly stable response even in the event of nu...

In this paper, we apply a so-called robust and perfect tracking (RPT) control technique to the design and implementation of the flight control system of a miniature unmanned rotorcraft, named HeLion. To make the presented work self-contained, we will first outline some background knowledge, including mainly the nonlinear flight dynamics model and the inner-loop flight control system design. Next, the highlight of this paper, that is, the outer-loop flight control system design procedure using RPT control technique, will be detailed. Generally speaking, RPT control technique aims to design a controller such that (i) the resulting closed-loop system is asymptotically stable, and (ii) the controlled output almost perfectly tracks a given reference signal in the presence of any initial conditions and external disturbances. Since it makes use of all possible information including the system measurement output and the command reference signal together with all its derivatives (if available) for control, RPT control technique is particularly useful for the outer-loop layer of an unmanned aircraft. Both simulation and flight-test results will be presented and analyzed at the end of this paper, and the efficiency of the RPT control approach will be evaluated comprehensively.

This paper presents the design and development of a fixed low-order, robustH2controller for a micro air vehicle (MAV) named Sarika-2. The controller synthesis uses strengthened discrete optimal projection equations and frequency-dependent performance index to achieve robust performance and stability. A single fixed gain low-order dynamic controller provides simultaneous stabilization, disturbance rejection, and sensor noise attenuation over the entire flight speed range of 16 m/sec to 26 m/sec. Comparative study indicates that the low-orderH2-controller achieves robust performance levels similar to that of full order controller. Subsequently, the controller is implemented on a digital signal processor-based flight computer and is validated through the real time hardware in loop simulation. The responses obtained with hardware in loop simulation compares well with those obtained from the offline simulation.

Algorithms for constructing parametric vector functions are considered to determine flight trajectories in the design calculations of flight vehicle weight parameters and flight characteristics, in the calculations of stability and required aerodynamic moments of the controlling and stabilizing surfaces when flying over the specified trajectory leg.

PurposeThe purpose of this paper is to identify linear model parameters of launch vehicles based on the actual flight test data. To compare the estimated parameters with the ones obtained by two other approaches: identification based on the recorded data from six‐degree‐freedom simulation of motion and linearization of the equations of motion via small‐disturbance theory as an analytical method.Design/methodology/approachAs the vehicle contains all the key issues in system identification such as time‐varying, unstable, nonlinear, and closed‐loop dynamics, Kalman filter method under the autoregressive with exogenous input model structure is used as a powerful method to estimate the dynamic parameters.FindingsSimulation results demonstrate that the linear model parameters used in the vehicle design and analysis should be validated by flight test data to accurate the vehicle dynamic model as more as possible.Practical implicationsOne of the most important usages of a linear model of aerospace vehicles is to design their controller. Another application of the algorithm presented in this paper is to estimate online dynamic parameters of the vehicle when they are required for the operation of the control system.Originality/valueBeing strongly affected by vehicle dynamic characteristics, linear model parameters of launch vehicles play important part in their design and analysis.

The longitudinal dynamic flight stability of a bumblebee in forward flight is studied. The method of computational fluid dynamics is used to compute the aerodynamic derivatives and the techniques of eigenvalue and eigenvector analysis are employed for solving the equations of motion. The primary findings are as the following. The forward flight of the bumblebee is not dynamically stable due to the existence of one (or two) unstable or approximately neutrally stable natural modes of motion. At hovering to medium flight speed [flight speed u e = (0–3.5) m s−1; advance ratio J = 0–0.44], the flight is weakly unstable or approximately neutrally stable; at high speed (u e = 4.5 m s−1; J = 0.57), the flight becomes strongly unstable (initial disturbance double its value in only 3.5 wingbeats).

The flight parameters of ChangGong-91, a light aircraft in the normal category, were estimated from flight tests. The output error method was used to produce aerodynamic coefficients, stability and control derivatives. A flight training device (FTD) was developed based on the estimated flight parameters. Flat earth, rigid body, and standard atmosphere were assumed in the FTD model. Euler angles were adapted for rotated state variables to reduce the computational load. Variations in flight Mach number and Reynolds number were assumed to be negligible. Body, wind, stability and inertial axes allow 6 second-order linear differential equations for translational and rotational motions. The equations of motion were integrated with respect to time, resulting in good agreement with the flight tests.

The fault detection problem is investigated for the morphing flight vehicle with different switched sweepback during flight. First, the flight dynamics is modeled as a switched system based on the theory of the multi-rigid-body and switched system. Then, the discrete model is presented by the theory of stochastic control theory. Also, the robust fault detection filter for the discrete switched control system is designed with H-/H ∞ performance index. Depending on multiple Lyapunov function and the average dwell-time method, we analyze the system stability and the sufficient existing conditions of filtered are derived in the form of LMIs. Finally, numerical examples based on Fire-Bee morphing flight vehicle are given to illustrate the efficiency of the proposed method.

The formation flight has many significant advantages over single vehicle flight. The control and tracking issues of lateral roll dynamics of two UAVs with leader-follower pattern is discussed in this paper. The objectives of this work is to develop the robust control technology using H ∞ techniques to withstand the lateral aero-coefficient-perturbed conditions in the control and tracking of two aerodynamically coupled UAVs in close formation flight. The work focuses on the flight control and tracking of roll dynamics and its decoupling from yaw dynamics. The follower lateral state space data modified by the upwash vortex aerodynamic effect is incorporated during the design phase of H ∞ controllers. The roll dynamics of leader UAV is tracked by the follower under perturbed conditions using Η ∞ controller within 0.05 degree error.

The hypothesis of this report is that delivery accuracy of small-diameter spin-stabilized projectiles can be improved through novel guidance and control techniques using low-cost components. A gyroscopically stable projectile equipped with a strap-down detector and rotary actuation assembly is introduced. Flight models are formulated to enable nonlinear simulation. The unique guidance challenges posed by characteristics of spin-stabilized flight dynamics such as limit cycles, center-of-gravity swerve, instability, and practical feedback are illustrated. New guidance and control techniques to circumvent these difficulties are proposed. Modeling, parameter estimation, and stability analysis results underpin control design. Representative feedback, control commands, and flight behaviors from nonlinear simulations demonstrate the efficacy of this guidance approach. Monte Carlo analysis shows more than a factor of two in accuracy improvement of the guided over the ballistic flight. These results indicate that delivery system improvements are achievable in small, gyroscopically stable projectiles containing low-cost guidance elements using integrated control formulations.

In this chapter, a fuzzy controller for unmanned aerial vehicle (UAV) flight dynamics is investigated. Fuzzy logic-based longitudinal and lateral controllers are designed. The fuzzy logic controller works well, even though no optimization technique is used to optimize the system and it was designed without dynamic model knowledge. In fuzzy logic controllers, a careful arrangement of membership functions may lead to better results. The stability of fuzzy controllers is also investigated. The effectiveness of different control methods for UAV flight control is compared in this chapter.

ADF or Automatic Direction Finder is one of the basic navigation machines which works based on the waves at low and medium frequencies. Tuning capacitors and selecting the appropriate circuit for each band embedded in receiver and is controlling by signals which are sending from the user from the controller section. Electromechanical systems of current receiver has reduced system performance in terms of size, weight, maintenance and accuracy of performance, and increases construction costs and the development of electronic instrumentation compared to the existing systems, the proposal design is based on electronic devices. In addition, due to the advantages of digital implementation in terms of accuracy, cost and ease of manufacturing, processing and detection of mixed signals, the choice of frequencies and the angle transmitter calculating is implemented by the digital transmitter.

As hypersonic flight vehicle flying at a high altitude where aerodynamic forces and moments are not enough for steady flight, reaction control system is widely used due to its effectiveness and agility. This paper describes two main approaches to studying the effect of reaction control system. The first approach is the method by measuring the pressure near the thrusters and then estimating the gas-jet interaction. The second one is the method by using moment system identification to identify the aerodynamic force caused by reaction control system. The second approach can be easily used without adding extra measurements. And identification method of the time parameters in the reaction control system is also discussed.

The fly-around guidance control problem for non-cooperative target in orbital space is studied in this paper, in which only the relative angle measurement information and the space flight vehicle own motion information are available. We first established the mathematical model of the fly-around problem to describe the relative motion between a flight vehicle and its target, and the circumnavigation control problem is formulated as a math problem. Then, we design a control law of fly-around process and the convergence of the control law is also proved. Finally, the effectiveness of the proposed circumnavigation control design law is shown by some numerical simulation results.

In this paper, according to many kinds of hardware-in-the-loop (HIL) simulation systems, especially for the one setting controller as the hardware part, a general HIL development platform was constructed. This platform is consisted of serial input and output communication models, which can be widely used in many kinds of Unmanned Aerial Vehicle (UAV) HIL simulation systems. Changing the UAV model in Simulink and control algorithm in hardware, a new HIL simulation model will be built. This paper references a HIL simulation platform for Rotary-Wing Unmanned Aerial Vehicle (RUAV) developed by Shenyang Institute of Automation, Chinese Academy of Science, then properly modified the communication models and successfully applied them on the Fixed-Wing UAV (FUAV) HIL simulation platform. The HIL method is an effective way to construct a more realistic development platform. The system constructed in this paper not only uses the hardware equipment as the control unit, but also represents the FUAV dynamics model in the Matlab/Simulink environment. Besides, this system also brings in the FlightGear interfacing software to help testers obviously observe the flight state changes. This development pattern brings many advantages for developing the flight dynamics models and controllers of different kinds of UAVs. Results from HIL and realistic flight simulation promote the development, improvement, and realization processes of the UAV flight control algorithms and meanwhile assess the adequacy of the flight model.

Proper design of the flight controller of an unconventional unmanned aerial vehicle requires highly stable performance, as well as reliable computer aided tools. Such tools provide simulation process that is based on classical control design. This paper describes the development of flight control design and simulation process, which can be applied to vehicles of a wide range of classes. The design process is based on single input/single output flight dynamics modeling and simulation using Matlab/Simulink, Visual C# dotNet and Microsoft Flight Simulator on a local area network environment. The proposed tool provides solution of flight dynamics that can be used by designers of parameterized vehicle UAV models and offers efficient simulation means for specific use cases. SAHIL program is intended as a simulator used for tuning the controller parameters in linear flight control for the SK1 vehicle. Thereby, it gives requirements for controller, simulation and analysis as computational design criteria. It facilitates successful testing of the design via simulation process to achieve high performance UAV controller design. The use of flight simulation tools greatly reduces the risk as well as the required amount of flight tests, particularly in complex and dense aerospace situations, which is a well-recognized benefit of such approaches.

This paper presents a model of a particular class of a convertible MAV with fixed wings. This vehicle can operate as a helicopter as well as a conventional airplane, i.e. the aircraft is able to switch their flight configuration from hover to level flight and vice versa by means of a transition maneuver. The paper focuses on finding a controller capable of performing such transition via the tilting of their four rotors. The altitude should remain on a predefined value throughout the transition stage. For this purpose a nonlinear control strategy based on saturations and Lyapunov design is given. The use of this control law enables to make the transition maneuver while maintaining the aircraft in flight. Numerical results are presented, showing the effectiveness of the proposed methodology to deal with the transition stage.

This paper deals with devising robust nonlinear control strategy for benchmark system of scaled Yak-54 Unmanned Aerial Vehicle. Authors considered the applications of sliding mode controllers to the longitudinal flight dynamics of the Yak-54 UAV for executing maneuvers over full flight envelope. Unlike the classical technique of the two sliding surfaces for the two loops a single surface is selected for the level flight. Control of unmanned aerial vehicle involves the problem of incomplete measurements, modeling uncertainties and external disturbances which makes flight dynamic analysis and control system design difficult. We present an innovative robust control strategy based on powerful tools provided by the theory of sliding mode control algorithms. First order sliding mode controller are designed but they provide chattering at the control input thus a non linear second order super twisting controller is used to provide chattering free control with improved robust stabilization.

This paper presents the flight path angle tracking control of the longitudinal dynamics of a generic hypersonic flight vehicle(HFV). Due to the use of digital computers and microprocessors for controls applications, the discrete hypersonic flight control is investigated. The altitude command is transformed into the flight path angle information. The back-stepping scheme is applied for the attitude subsystem which includes flight path angle, pitch angle and pitch rate. The virtual control is designed with nominal feedback and Neural Network (NN) approximation. To use the information of throttle setting, the multi-rate sampling method is employed for the two subsystems where the velocity subsystem is considered as slow dynamics. Under the proposed controller, the semiglobal uniform ultimate boundedness (SGUUB) stability is guaranteed. The simulation is presented to show the effectiveness of the proposed control approach.

Future spacecraft are envisioned as autonomous, miniature, and intelligent space systems. This paper describes the design and implementation of a model predictive control (MPC) system for satellite attitude control. The MPC algorithm is designed to successfully deal with constraints due to the small control torque given by magnetic torquers and the Earth’s magnetic field. Laguerre functions are proposed to simplify the implementation of the MPC controller for on-line computation. A control system processor is designed as a peripheral hard core of the system-on-chip for satellite on-board data handling. Targeting the FPGA technology, this processor runs up to 120 MHz.

This paper represents an efficient technique for neural network modeling of flight and space dynamics simulation. The technique will free the neural network designer from guessing the size and structure for the required neural network model and will help to minimize the number of neurons. For linear flight/space dynamics systems, the technique can find the network weights and biases directly by solving a system of linear equations without the need for training. Nonlinear flight dynamic systems can be easily modeled by training its linearized models keeping the same network structure. The training is fast, as it uses the linear system knowledge to speed up the training process. The technique is tested on different flight/space dynamic models and showed promising results.

This paper encompasses a study on the modelling, design and simulation of a motion platform for a flight simulator. The motion platform has a hexapod configuration with six degrees-of-freedom, designed on a biologically inspired concept. A dynamical model of the proposed motion platform is formulated using the principles of flight simulation and Stewart platform modeling. In the first test case, the proposed dynamical model is evaluated in terms of motion requirements for a Level-C flight simulator through real-time simulations using SimMechanics and xPC Target software. X-Plane (a commercial flight simulator package) is used to provide the flight dynamical model for a Level-C flight simulator. In the second test case, a computed torque-based controller incorporating the proposed dynamical model is tested in both forward and inverse dynamics modes to track the flight dynamics of an aircraft. Finally, the paper draws conclusions about the significance and performance of the proposed system in terms...

Nomenclature AND = Alphanumerical Display AOCS = Attitude and Orbit Control Satellite EPS = EUMETSAT Polar System FDF = Flight Dynamics Facilities FOM = Metop Flight Operation Manuel GRNDCON = Ground Controller LEO = Low Earth Orbit MCS = Mission control system MPF = Mission Planning Facilities PI = Procedure Initiator PLM = PayLoad Module SVM = SerVice Module SCP = System Controller Procedure SPACON = Space Controller SOE = Spacecraft Operations Engineer STOL = Satellite Test and Operation Language SIOV = Satellite In Orbit Verification

This paper presents a flight control design for longitudinal motion of helicopter to establish autopilot techniques of helicopter-type unmanned aerial vehicles (UAVs). The characteristics of the linearized equation of the helicopter is changed during a specified flight mission because the trim values of the nonlinear equation are also varied. In this paper, the longitudinal motion of the helicopter is modeled by a linear interpolative polytopic model whose varying parameter is the flight velocity. A flight control systems with a gain scheduling state feedback law is designed to stabilize the vehicle and track a reference which realizes the flight mission. The effectiveness of the proposed flight control system is evaluated by computer simulation.

Historically, aircraft longitudinal control has been realized by means of two loops: flight path (the control variable is elevator displacement) and speed control (the control variable is propulsive thrust or engine power). Both the elevator and throttle control cause coupled altitude and speed response, which exerts negative effects on longitudinal flight performance of aircraft, especially for Terrain Following(TF) flight. Energy-based method can resolve coupled problem between flight speed and path by controlling total energy rate and energy distribution rate between elevator and throttle. In this paper, energy-based control method is applied to design a TF flight control system for controlling flight altitude directly. An error control method of airspeed and altitude is adopted to eliminate the stable error of the total energy control system when decoupling control. Pitch loop and pitch rate feedback loop are designed for the system to damp the oscillatory response produced by TF system. The TF flight control system structure diagram and an aircraft point-mass energy motion model including basic control loops are given and used to simulate decoupling performance of the TF fight control system. Simulation results show that the energy-based TF flight control system can decouple flight velocity and flight path angle, exactly follow planned flight path, and greatly reduce altitude error, which is between +10m and -8m.

High Intensity Radiated Field (HIRE) conditions may cause sensor and/or controller failure in flight control system. In this paper, a flight dynamics imitation scheme is proposed to establish the failure tolerance of sensors in Electro-Magnetic Environment (EME).

This paper describes recent results on the design and simulation of a flight control strategy for the micromechanical flying insect (MFI), a 10-25 mm (wingtip-to-wingtip) device capable of sustained autonomous flight. Biologically inspired by the real insect's flight maneuver, the wing kinematics are paremetrized by a small set of parameters which are sufficient to generate desired average torques to regulate its attitude. Position control was achieved through attitude control based on the linearized dynamics under small angle assumption near hovering. During its continuous flight, the controller schedules the desired wing kinematic parameters according to the inverse map based on the feedback error at the end of each wingbeat. The proposed controller was simulated with the Virtual Insect Flight Simulator, and the results show convergence of both position and orientation.