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This article proposes an adaptive trajectory tracking control scheme for low-speed car-like vehicles with less efforts in tuning of the control gains. An interesting way of integrating adaptive control gains with consideration of steering saturation by using the backstepping technique is designed to enhance trajectory tracking while ensuring the commanded inputs within the input boundaries. The design of such adaptive control gains is also based on enhancing the convergence rate of tracking errors, especially for lateral deviation from the reference trajectory. It is further theoretically proven that, even under the influence of steering saturation, the proposed controller can make the closed-loop system approximately globally asymptotically stable at zero errors. Comparative MATLAB/Simulink simulations and experimental tests based on Quanser latest self-driving car have been conducted to verify the effectiveness of the proposed control scheme in accurate tracking without violating the input constraints. [ABSTRACT FROM AUTHOR]

This article considers the decentralized fractional-order fault-tolerant control problem for unmanned aerial vehicles (UAVs) against wind disturbances and actuator faults in a directed communication network. A new composite adaptive disturbance observer-based decentralized fractional-order fault-tolerant control (CADOB-DFO-FTC) scheme, which incorporates fractional-order (FO) sliding-mode surfaces, nonlinear disturbance observers (NDOs), fuzzy wavelet neural networks (FWNNs), and robust controllers, is developed to achieve the attitude tracking control of networked UAVs in a decentralized way. Based on the FO sliding-mode surfaces, the NDOs are first developed to estimate the lumped uncertainties due to the aerodynamic parameter perturbations, wind disturbances, and actuator faults. Then, adaptive FWNNs with updating weighting matrices, mean vectors, and deviation vectors are constructed to effectively attenuate the adverse effects induced by the NDO estimation errors. Furthermore, to compensate the FWNN approximation errors, robust controllers are integrated into the developed control scheme to enhance the approximation abilities. It is shown that by using Lyapunov methods, all UAVs can track their attitude references. Finally, comparative simulation results are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The sizes of wind turbines have been steadily increasing over the past decade, especially on offshore sites. The greater structural flexibility of such machines necessitates the development of reliable load mitigation techniques to alleviate the effects of asymmetric wind loads and fatigue. Given the importance of such techniques, this article proposes a reliable load mitigation scheme, referred to as “fault-tolerant individual pitch control,” for individually adjusting the pitch angle of wind turbine blades in the presence of blade pitch actuator faults. The proposed scheme consists of a collective pitch control augmented with an individual pitch control, and a fault detection and diagnosis system. Simulation results using an offshore wind turbine illustrate the effectiveness as well as fault-tolerance capability of the developed scheme compared to controlling the pitch angles collectively. The developed scheme not only ensures an almost equal output power with reduced loads on the turbine, but also tolerates the effects of possible faults in pitch actuators of the blades. [ABSTRACT FROM AUTHOR]

The current maritime applications have yielded strong demands for the development of advanced unmanned surface vehicles (USVs) with more reliable path following capabilities to greatly extend mission durations and enhance accommodative capabilities of USVs to more hazardous and dynamic environments. This paper presents an adaptive path following control method using a retrofit adaptive tracking control technique with application to a USV with consideration of environmental disturbances (like winds, waves, and currents), while taking into account of the system constraints of USVs, including both turning features (turning rate limit and turning dynamics) and rudder operation constraints (rudder deflection and rate saturation, and its dynamics). In order to guarantee the satisfactory performance of the USV operating in a calm environment, a baseline state feedback tracking controller considering the characteristics of yaw rate and rudder operations, and USV steering and actuator dynamics is first designed. In the presence of time-varying environmental disturbances, a retrofit adaptive disturbance compensating control mechanism is then developed based on the disturbance amplitude estimated from an indirect adaptive disturbance estimator. Finally, a reconfigurable adaptive path following controller is synthesized by combining the baseline controller and the adaptive disturbance compensating mechanism for the proper operation of the USV in the presence of environmental disturbances, while the desired path is successfully followed by the USV within an acceptable deviation boundary and without violating constraints of turning rates as well as amplitude and rate of rudder deflections. To evaluate the effectiveness of the proposed path following control methodology, both numerical simulations on a nonlinear USV model and field experiments on a real-size USV are conducted. [ABSTRACT FROM AUTHOR]

This paper presents an average dwell-time method for fault-tolerant control of a class of uncertain switched linear time-delay systems and also designs an algorithm to determine the parameters pertaining to the dwell-time condition. Compared to the literature results, this paper features the following: 1) the proposed method is independent of switching polices if switchings are slow enough in the average sense; 2) the proposed control design guarantees exponential stabilization of this class of time-delay linear systems with actuator faults; and 3) this method treats all actuators in a unified manner without a need to identify which are faulty or healthy actuators. The proposed method is applied to the water pollution control problem, for the first time, to deal with different ratios of stream flow rates to effluent flow rates. [ABSTRACT FROM AUTHOR]

This paper proposes a novel adaptive sliding-mode-based control allocation scheme for accommodating simultaneous actuator faults. The proposed control scheme includes two separate control modules with virtual control part and control allocation part, respectively. As a low-level control module, the control allocation/reallocation scheme is used to distribute/redistribute virtual control signals among the available actuators under fault-free or faulty conditions, respectively. In the case of simultaneous actuator faults, the control allocation and reallocation module may fail to meet the required virtual control signal, which will degrade the overall system stability. The proposed online adaptive scheme can seamlessly adjust the control gains for the high-level sliding mode control module and reconfigure the distribution of control signals to eliminate the effect of the virtual control error and maintain the stability of the closed-loop system. In addition, with the help of the boundary layer for constructing the adaptation law, the overestimation of control gains is avoided, and the adaptation ceases once the sliding variable is within the boundary layer. A significant feature of this study is that the stability of the closed-loop system is guaranteed theoretically in the presence of simultaneous actuator faults. The effectiveness of the proposed control scheme is demonstrated by experimental results based on a modified unmanned multirotor helicopter under both single and simultaneous actuator faults conditions with comparison to a conventional sliding mode controller and a linear quadratic regulator scheme. [ABSTRACT FROM PUBLISHER]

This paper presents the development of a nonlinear model predictive controller (NMPC) applied to a closed grinding circuit system in the cement industry. A Markov chain model is used to characterize the cement grinding circuit by modeling the ball mill and the centrifugal dust separator. The probability matrices of the Markovian model are obtained through a combination of comminution principles and experimental data obtained from the particle size distribution of cement samples at specific stages of the system. The NMPC is designed as a supervisory controller to manage distributed controllers installed in the process. Both the model and the controller are validated online through the implementation of the proposed approach in the supervisory control and data acquisition (SCADA) system of an industrial plant. The results show a significant improvement in the performance of the grinding circuit in comparison to the operation of the system without the proposed controller. [ABSTRACT FROM PUBLISHER]

Presents a study which discussed a multiple-model (MM) estimator with a variable structure called likely-model set algorithm applied to hybrid estimation problems. Impact of (M) estimation to adaptive estimation; Conclusions.

Investigates the importance in the application of a variable-structure multiple-model (VSMM) estimator, called model-group switching (MGS) algorithm. Design of model-group switching algorithm; Design of test scenarios between MGS algorithm with the Interacting Multiple-Model estimator; Performance measures of MM estimators.

Presents information on the detection and diagnosis of sensor and actuator failures, using an approach which is based on the interacting multiple-model (IMM) estimation algorithm. Examination of modern engineering systems; Details on the integrated framework of this approach; Conclusions of this research.

Presents a fast learning algorithm for training multilayer feedforward neural networks (FNN) by using a fading memory extended Kalman filter (FMEKF) along with a technique using self-adjusting time-varying forgetting factor. Overview of the FEMKF-based learning algorithm; U-D factorization-based FMEKF learning algorithm; Applications to nonlinear systems modeling.

This article details the development and evaluation of a practical solution for path-constrained proximity maneuvers of spacecraft. Whereas no velocity measurement is utilized within the feedback structure, the controller rigorously enforces actuator magnitude constraints. Specifically, the control algorithm is constructed from a potential function method repelling the spacecraft from possible collisions. The proposed controller can guarantee potential functions to be navigated to the origin and thus overcome the stubborn local minima problem. Moreover, the control capability under any given control limit can be estimated and adjusted by changing the feedback gains. The specific performance with guaranteed safety can be also explicitly calculated by designers. The results are obtained through a Lyapunov-based stability analysis to prove uniformly ultimate boundedness. Numerical simulation results illustrate the performance and features of the developed control method. [ABSTRACT FROM AUTHOR]

In a dynamic environment, moving to the destination safely and effectively is of paramount importance for an unmanned ground vehicle (UGV). This article presents a strategy of trajectory planning and tracking that aims to ensure the UGV’s safety in an uncertain environment. Specifically, based on the initial environment information, a global optimal trajectory connecting the start and the destination is predefined by an artificial fish swarm algorithm (AFSA). In the presence of unforeseen obstacles, a trial-based forward search (TFS) algorithm based on the Markov chain is proposed in the local trajectory planning module, while collision prediction is integrated as heuristic information. The vehicle’s current state is updated accordingly for the sake of avoiding entire state spaces involved in the computation. Therefore, the storage efficiency and convergence rate in local path planning are sufficiently enhanced in comparison to dynamic programming. Moreover, command signals can be calculated with the proposed multiconstrained model predictive controller (MMPC), ensuring the vehicle to track the reference trajectory and smoothen the motion. Finally, the results in both simulations and experiments reveal the effectiveness of the proposed algorithm in the presence of both static and dynamic obstacles. Note to Practitioners—This article is motivated by the unmanned ground vehicle (UGV) collision avoidance problem in practical missions, such as farming and emergency response. In recent years, various trajectory planning and tracking algorithms have been widely developed. However, the environmental complexity and the intruders’ unexpected movement pose difficulties in trajectory planning, especially in ensuring the computation time under the allowable threshold. Moreover, the UGV practical trajectory tracking is a challenging task which demands a desired response within various physical constraints. In this article, a two-stage conflict resolution system is proposed. First, a trial-based forward search (TFS) is used to generate a new trajectory deviating the UGV from the initially generated trajectory by the artificial fish swarm algorithm (AFSA), aiming to avoid the unforeseen intruders (unknown in prior) in real-time. Using these two trajectory planning algorithms alternatively, both global trajectory optimality in a cluttered environment and appropriate maneuvers with respect to unexpected intruders can be achieved. Subsequently, the UGV is modeled according to its kinematic characteristics, and thus a multiconstrained model predictive controller (MMPC) is designed to follow the reference trajectory. The physical constraints are respected by integrating them into the controller. Simulations and experimental results demonstrate that the proposed strategy can guide and control a UGV from the start to the destination safely and smoothly, even in the case of multiple obstacles with constant or varying velocities. Furthermore, the proposed collision avoidance strategy can be extended to other unmanned systems, including unmanned aerial vehicles and unmanned surface vehicles. [ABSTRACT FROM AUTHOR]

In recent decades, deep learning (DL) has become a rapidly growing research direction, redefining the state-of-the-art performances in a wide range of techniques, such as object detection and speech recognition. In the aircraft design, dynamics, and control field, many works hinge on the information-rich data-driven approach, which includes the fusion-based prognostic and health management, the airliner's flight safety monitoring, intelligent sensing, and flight control systems development. While DL provides great potentials to solve these data-driven problems, a systematic review and discussion as to how the DL has been/can be used for these problems are still missing in relation to the rapidly developing and widely used DL techniques. In this article, we aim to address this urgent issue to provide a timely overview of the state-of-the-art for applying DL to the aircraft design, dynamics, and control field. In particular, we briefly introduce five representative DL methods, i.e., deep neural network, deep autoencoder, deep belief network, convolutional neural network, and recurrent neural network. Mathematical definitions for each method are presented, and illustrative applications are also discussed. We then review the existing DL-based works that have appeared in the aircraft design, dynamics, and control field. The review efforts are divided into two major groups, i.e., the own-ship aircraft modeling, wherein the works have been/can be implemented online for the aircraft design/dynamics/control, and other airplanes research works, wherein DL-based schemes provide offline monitoring of the aircraft operation. We then summarize the data sources and DL architectures. Referring to the experiences of DL research works/techniques development in other related fields, future opportunities, challenges, and potential solutions for implementing DL in the aircraft design, dynamics, and control field are also discussed. [ABSTRACT FROM AUTHOR]

This article presents a fixed-time accommodation strategy of actuator faults for hypersonic gliding vehicles (HGVs). The approach against actuator faults is incorporated by sliding mode control (SMC), bilimit homogeneity, and adaptive techniques, with consideration of practical constraints and model uncertainties. The resulting fault-tolerant attitude control law allows the fault compensation to be completed in a fixed time, in view of the limited time available for recovery of a faulty HGV. The effectiveness of the presented scheme is validated by comparing it to the finite-time fault accommodation scheme. Note to Practitioners—Hypersonic vehicles have drawn significant interests due to the features of super-fast and flexible maneuverability. The use of advanced fault-tolerant control (FTC) techniques is expected to guarantee safety during hypersonic vehicle operation. A challenging problem is how to counteract actuator faults promptly and effectively in the presence of practical constraints and model uncertainties. This article presents a fixed-time FTC algorithm for a hypersonic gliding vehicle. [ABSTRACT FROM AUTHOR]

A fault-tolerant formation control (FTFC) strategy is proposed against severe actuator faults, applied to a team of wheeled mobile robots (WMRs). In the beginning, a team of WMRs is operating in a prescribed formation topology. As long as the robot(s) cannot complete the required mission due to severe actuator faults, the formation is reconfigured for the healthy WMRs to eliminate the fault effects. The new reconfiguration is determined by means of an optimal assignment scheme so that each healthy robot can be assigned to a unique position. Subsequently, each robot starts planning its trajectory to reach its new position in the new formation configuration by virtue of a hybrid genetic algorithm and particle swarm optimization (GA–PSO). As metaheuristic optimization techniques, such as GA and PSO, are unable to solve the optimization problem with continuous control inputs, control parameterization and time discretization (CPTD) method is, therefore, adopted to offer an approximate piecewise linearization of the control inputs. Thus, an approach with the integration of CPTD and GA–PSO is developed. This integrated approach enables that the time of achieving the configuration is minimized, while the physical constraints of WMRs and collision avoidance are explicitly considered. Finally, real-time experiments are conducted to validate the effectiveness of the proposed algorithm compared with other optimization techniques, such as GA and PSO. Note to Practitioners—Cooperative unmanned systems have drawn significant interests in military and civilian applications. During missions’ execution, it is of great importance for cooperative unmanned systems to have fault-tolerance capabilities for achieving the desired mission when faults occur in one or more team members. A challenging problem is how to detect and isolate the fault and how to mitigate the fault effects on the whole mission. This article presents a fault-tolerant formation control strategy in the case of severe actuator fault occurrence in a team of wheeled mobile robots. [ABSTRACT FROM AUTHOR]

In this paper, a quasi-optimal higher order sliding mode control (HOSMC) scheme is designed using disturbance observer (DOB) and adaptive techniques. The overall HOSMC scheme is constituted by three portions: 1) a switch-based quasi-optimal control law that ensures rapid finite-time stabilization of the origin, producing a nominally uncertainty-free system, based on a perturbed chain of integrators; 2) a DOB which estimates the lumped uncertainties with lower frequencies; and 3) an adaptive controller designed to deal with the fast-varying terms of these lumped uncertainties over the pass-band of the DOB. Since the adaptive controller and the DOB work in a cooperative manner, the only requirement is that the switching gain be greater than the bound of the DOB estimation error, instead of the bound of the lumped uncertainties. As a consequence, overestimation in the adaptive controller can be avoided by resorting to the equivalent control. Simulation results confirm the capabilities of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper proposes a fault-tolerant control (FTC) scheme for a hypersonic gliding vehicle to counteract actuator faults and model uncertainties. Starting from the kinematic and aerodynamic models of the hypersonic vehicle, the control-oriented model subject to actuator faults is built. The observers are designed to estimate the information of actuator faults and model uncertainties, and to guarantee the estimation errors for converging to zero in fixed settling time. Subsequently, the finite-time multivariable terminal sliding mode control and composite-loop design are pursued to enable integration into the FTC, which can ensure the safety of the postfault vehicle in a timely manner. Simulation studies of a six degree-of-freedom nonlinear model of the hypersonic gliding vehicle are carried out to manifest the effectiveness of the investigated FTC system. [ABSTRACT FROM PUBLISHER]

This article proposes a safety control scheme for quadrotor unmanned aerial vehicle (UAV) to counteract ground effect and blade damage. The impacts of ground effect and blade damage are quantitatively analyzed in the established model. The proposed safety control scheme consists of position and attitude loops. Specifically, a proportional and derivative controller is designed as a baseline control with acceleration feedforward in the position loop. A disturbance observer (DO) using the measured Euler angles is exploited to estimate the lumped disturbance forces. The developed DO can effectively mitigate the estimation deviation caused by the angle tracking error. Subsequently, differential flatness theory is used to obtain the Euler angle references and the derivatives. In the attitude loop, sliding mode control and fixed-time sliding mode observer (SMO) are integrated to deal with ground effect and blade damage promptly. To demonstrate the effectiveness of the proposed safety control scheme, flight experiments are carried out, where the quadrotor UAV flies close to the rugged ground in the presence of blade damage. [ABSTRACT FROM AUTHOR]

Focusing on a quadrotor unmanned aerial vehicle (UAV), the presence of unintended actuator faults and external disturbances increases the risk of a crash. Although plenty of efforts have been devoted, how to integrate capability analysis into safety control design is still an open issue. This article presents the design of a safety control system for quadrotor UAVs. Firstly, a system capability analysis method based on a differential flatness algorithm is developed, so that the derivatives (i.e., velocity, jerk, and snap) of flight trajectory can be formulated as flat variables. A tradeoff between system capability and permissible flight maneuverability is made to avoid actuator saturation. Secondly, dual-loop nonlinear disturbance observers are exploited to identify the actuator faults and disturbances, which can thereby be handled by a cascade control scheme. Moreover, the trajectory is regenerated online at the expense of degraded flight maneuverability or even emergency landing, in view of the remaining actuator control authority. When comparing to the existing methods, the gap among safety control, trajectory generation, and system capability analysis is bridged to ameliorate practical flight safety. Finally, flight tests are carried out to demonstrate the unique merits of the proposed system. [ABSTRACT FROM AUTHOR]

This article focuses on the 3-D guidance strategy for a reusable launch vehicle (RLV) during terminal area energy management (TAEM) phase. Based on sliding-mode and shrinking-horizon techniques, the proposed scheme consists of trajectory generation and correction mechanisms, which can enhance the guidance precision and robustness against disturbances. The RLV guidance model, in the form of a set of highly nonlinear differential equations in the time domain, is recast as an altitude-domain model. By this means, the main characteristics of TAEM gliding motion are extracted. The altitude-domain model is thereby used for trajectory generation. A sliding surface and a guidance law are proposed. Hybrid TAEM constraints can be fully satisfied when the proposed guidance law drives the altitude-domain vehicle model to the designated altitude. Using the proposed guidance law as the input of the altitude-domain model, a constrained TAEM trajectory is generated, leading to TAEM guidance commands simultaneously. The commands are utilized to drive the time-domain model to the terminal target. In an attempt to compensate for model uncertainties and initial deviations, the guidance commands are modified periodically by the shrinking-horizon correction mechanism according to current states. Simulations on different scenarios are provided to demonstrate the performance of the proposed guidance strategy. [ABSTRACT FROM AUTHOR]

This work presents a new approach for designing decentralized receding horizon controllers (DRHC) for cooperative multiple vehicle systems with inter-vehicle communication delays arising from communication failures. Using DRHC each vehicle plans its own state trajectory over a finite prediction time horizon. The neighboring vehicles then exchange their predicted trajectories at each sample time to maintain cooperation objectives. Such communication failures lead to large, inter-vehicle communication delays of exchanged information. Large inter-vehicle communication delays can potentially lead to degraded cooperation performance and unsafe vehicle motion. To maintain desired cooperation performance during faulty conditions, the proposed fault-tolerant DRHC architecture estimates the tail part of the neighboring vehicle trajectory that is unavailable due to communication delays. Furthermore, to address the safety of the team against possible collisions during faulty situations, a fault-tolerant DRHC is developed, which provides safety using a safe protection zone called a tube around the trajectory of faulty neighboring vehicles. The radius of the tube increases with communication delay and maneuverability. A communication failure diagnosis algorithm is also developed. The required communication capability for the fault-diagnosis algorithm and fault-tolerant DRHC suggests a hierarchical fault-tolerant DRHC architecture. Simulations of formation flight of miniature hovercrafts are used to illustrate the effectiveness of the proposed fault-tolerant DRHC architecture. [ABSTRACT FROM AUTHOR]

A fault-tolerant control approach without rate sensors is presented for the attitude stabilization of a satellite being developed. External disturbances, reaction wheel faults, actuator saturation, and unavailable angular velocity are addressed. A sliding-mode observer is proposed by using attitude feedback only, and the unavailable angular velocity is estimated by this observer in finite time. Using the attitude and the estimated velocity, another sliding-mode observer is proposed to reconstruct actuator faults and disturbances. It is proven that reconstruction with zero observer error is achieved in finite time. With the reconstructed value, a velocity-free controller is then developed to asymptotically stabilize the attitude. Simulation results are also provided to verify the effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]