Search

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]

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 article investigates the fault‐tolerant containment control (FTCC) problem for a group of fixed‐wing unmanned aerial vehicles with simultaneous considerations of faults and collision avoidance. A fractional‐order (FO) FTCC scheme is established to steer all follower UAVs into the convex hull formed by the leader UAVs with the involvements of FO calculus, disturbance observers (DOs), and interval type‐2 fuzzy neural networks (IT2FNNs). In the proposed control protocol, FO sliding‐mode surfaces with artificial potential functions are first designed to revamp the filtered containment errors. Then, the DOs with FO calculus are constructed to estimate the FO lumped disturbances due to faults and external disturbances. Moreover, to compensate for the DO estimation errors, IT2FNN learning mechanisms are introduced to improve the FTCC capability. It is shown by Lyapunov stability analysis that all follower UAVs can successfully converge into the convex hull spanned by the leader UAVs without collisions even when a portion of UAVs is encountered by faults. Simulation results are presented to show the effectiveness of the developed control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates a new finite-time fault-tolerant control (FTC) using a fractional-order backstepping iterative design strategy for a fixed-wing unmanned aerial vehicle (UAV) in the presence of actuator faults and input saturation. To compensate for the lumped disturbance induced by the actuator faults, a neural network disturbance observer (NNDO) with finite-time observation capability is first developed as the fault diagnostic unit. Then, based on the diagnosed fault information, fractional-order (FO) calculus is artfully utilized to enhance the FTC performance within the backstepping design architecture. The salient feature of the developed control scheme is that the finite-time NNDO and FO calculus are simultaneously used to significantly increase the FTC performance against unexpected actuator faults. Moreover, to address the input saturation problem, the faulty UAV dynamics is augmented by a new auxiliary system. Furthermore, a Nussbaum function is incorporated into the FTC scheme to further avoid the calculation of the inverse gain matrix involved within the auxiliary system. It is shown by Lyapunov analysis that the tracking errors are convergent in finite time. Finally, comparative simulations are conducted to show the effectiveness of the developed FTC scheme. Some hardware-in-the-loop (HIL) experimental results are illustrated to further demonstrate the feasibility of the proposed finite-time fractional-order fault-tolerant control (FTFOFTC) method. [ABSTRACT FROM AUTHOR]

This paper proposes a fault-tolerant cooperative control (FTCC) scheme for multiple UAVs in a distributed communication network against input saturation, full-state constraints, actuator faults, and unknown dynamics. Firstly, by considering physical limitations, an auxiliary control signal is designed to simplify the analysis process. Secondly, to avoid the difficulty in the back-stepping design caused by full-state constraints, virtual control signals are constructed to transform constrained variables, while the dynamic surface control is adopted to avoid the phenomenon of "differential explosion." Thirdly, a disturbance observer (DO) is designed to estimate the unknown uncertainty caused by parameter uncertainty and actuator fault. Moreover, a recurrent wavelet fuzzy neural network (RWFNN) is used to compensate for the estimation errors of DO. Finally, it is proved that all states are uniformly ultimately bounded (UUB) by Lyapunov and invariant set theory. The effectiveness of the proposed scheme is further demonstrated by the simulation results. [ABSTRACT FROM AUTHOR]

In order to counteract actuator faults in formation flight of multiple unmanned aerial vehicles (UAVs), this paper presents a fault-tolerant formation control (FTFC) design methodology, in which the reference generator and the finite-time convergence of FTFC gains are explicitly considered. Feasible references in response to actuator faults can be generated by considering the health and mission conditions of an overall team of UAVs. Moreover, by applying an auxiliary integrated regressor matrix and vector method, FTFC gains can converge within a finite amount of time to facilitate the fault accommodation process. Thus, the negative effects resulting from failed actuators can be compensated by the healthy/redundant actuators in UAVs. Simulation studies of UAV formation flight are carried out to exemplify the effectiveness of this design approach. [ABSTRACT FROM AUTHOR]

This paper presents new design methodology and performance comparison of two hybrid fault-tolerant control (FTC) schemes applied to the regulation of the frequency and voltage amplitude of a diesel engine generator installed in a microgrid. Both of them are based on a unique combination of a model reference adaptive control (MRAC) with a proportional-integral-derivative (PID) controller and artificial intelligence techniques, i.e. artificial neural networks (ANN) and genetic algorithms (GA). Since in an islanded microgrid, the frequency of the system is determined by the shaft speed of the diesel engine (DE), while the voltage amplitude is set by the synchronous generator (SG) field voltage, therefore, two FTC systems for frequency and voltage regulation have been implemented in each proposed control scheme. The first scheme consists of an MRAC system with a PID controller tuned by a GA for controlling the speed of the DE and a classic MRAC system for controlling the voltage amplitude of the SG. In the second scheme, an MRAC system with a GA-tuned PID controller is used for the DE, and a hybrid controller in which the MRAC is combined with an ANN and a PID controller tuned by a GA is designed for the SG. The dynamic models of the microgrid components are presented in detail, and the proposed microgrid and its FTC systems are implemented and tested in the Simpower Systems of MATLAB/Simulink® simulation environment. All results indicate high effectiveness and robustness of the MRAC-based FTC schemes in both normal and emergency/faulty operations of the microgrid in comparison with a benchmark baseline controller, IEEE Type 1 AVR for the SG and a PID controlled governor for the DE. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This article presents a single‐hidden‐layer feedforward network (SLFN) aided fault‐tolerant control (FTC) scheme for a class of nonlinear systems subject to actuator faults. First, the upper bounds of the norms of the unknown functions, which cover information of actuator faults and amplitude saturation degrees, are deployed. The upper bounds are approximated by SLFNs with adaptive techniques. Subsequently, a sliding mode control approach is presented to allow for prompt corrective reactions, with explicit consideration of multivariable conditions and control input constraints. Finally, simulation results based on a nonlinear Boeing 747 aircraft model are presented to demonstrate the effectiveness of the proposed FTC scheme. [ABSTRACT FROM AUTHOR]

This paper explores the fault-tolerant control (FTC) problem for full-state error constrained attitude tracking of an uncertain spacecraft. The existing FTC solutions to this problem generally rely on an uniform strong controllability (USC) assumption that may not hold in the presence of multiplicative actuator faults. In this work, a sufficient condition for the USC assumption is presented to help evaluate the applicability of existing FTC solutions. Then, based on the unified error transformation method and symmetric barrier Lyapunov functions, a saturated adaptive robust FTC algorithm is proposed, which can eliminate the USC assumption without requiring the multiplicative actuator faults to be differentiable, while ensuring that (i) full-state error constraints are never violated; (ii) all closed-loop signals are bounded, despite the simultaneous presence of inertia uncertainties, disturbances, and actuator faults. Finally, simulation results are provided to verify our theoretical findings. [ABSTRACT FROM AUTHOR]