An active optimal fault-tolerant control (FTC) scheme for a class of nonlinear systems in strict-feedback form in the presence of partial loss of actuator effectiveness faults is proposed, using backstepping design technique and adaptive dynamic programming (ADP) algorithm to compensate the effects of failure. The proposed FTC scheme consists of feedforward controller that achieve the objective of fault-tolerant and feedback optimal controller, which can guarantee the performance index function is minimized. Since fault estimation and control law parameters are updated online, the control system has an adaptive failure compensation capability so as to reconfigure the control law in real time in response to failure indications. Based on Lyapunov stability theory, the whole closed-loop system is guaranteed to be ultimately uniformly bounded. Finally, the effectiveness of the proposed method is demonstrated by simulation.

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This paper proposes a sliding-mode control (SMC) scheme for a class of linear parameter varying (LPV) systems subject to a loss of control effectiveness and external disturbance. The LPV model is transformed into the non-LPV model representation. The updating law for unknown time-varying fault and the disturbance estimator are designed. The novel sliding-mode fault tolerant control (FTC) law is presented by using estimated fault and estimated disturbance to compensate the effects of faults in both cases: the known and the partial known system matrices. The stability analysis of closed-loop system is performed on the Lyapunov theory. The main advantage of the proposed method is to circumvent solving on-line parameter-dependent nonlinear matrix inequalities, also to adapt to the changes of unknown parameter. The feasibility of the approach is illustrated by means of the simulation examples.

This article investigates the optimal consensus problem for unmanned aerial vehicle formation systems with actuator faults based on nonlinear multi-agent systems. Initially, for fault-free multi-agent system, the distributed optimal controllers are constructed based on the adaptive dynamic programming technique. A critic neural network is applied to approximate the solution of the nonlinear Hamilton–Jacobi–Bellman equations, in which the weight updating laws are built to guarantee the weight vectors of the critic neural network convergence. Second, the fault compensators and corresponding tuning laws are proposed to compensate for actuator faults. Through a combination of optimal controllers and fault compensators, the distributed optimal fault-tolerant controllers are obtained. Then, according to Lyapunov extension theorem, some stability criteria for ensuring the stability of the aircraft and the normal flight of the unmanned aerial vehicle formation are established in the event of an actuator failure. Finally, an example of an unmanned aerial vehicle formation system is introduced to verify the efficiency and reliability of the designed optimal fault-tolerant control scheme.

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