Generalized PI control design for a class of unknown nonaffine systems with sensor and actuator faults

This work deals with the tracking control problem of a class of unknown nonaffine dynamic systems that involve unpredictable sensor and actuation failures. As the control inputs enter into and influence the dynamic behavior of the nonaffine system through a nonlinear and implicit way, control design for such system becomes quite challenging. The underlying problem becomes even more complex if the system dynamics are unavailable for control design yet involving unanticipated sensor and/or actuator faults. In this work, a structurally simple and computationally inexpensive control scheme is proposed to achieve uniformly ultimately bounded (UUB) stable tracking control of a class of nonaffine systems. The proposed control is of a generalized PI form and is able to accommodate both sensor and actuator faults. The effectiveness of the proposed control strategy is confirmed by theoretical analysis and numerical simulations.     

Dynamic surface active fault tolerant control design for the attitude control systems of UAV with actuator fault

In this paper, an active fault tolerant control (FTC) approach based on transient performance index is proposed for the attitude control systems of unmanned aerial vehicle (UAV) with actuator fault. The nonlinear attitude control system model for UAV with actuator faults is given, which represents the dynamic characteristics of UAV. A fault diagnosis component is used for fault detection and estimation. According to the fault estimation information obtained during the fault diagnosis, the fault tolerant control scheme is developed by adopting the adaptive dynamic surface control technique, which guarantees the asymptotic output tracking and ultimate uniform boundedness of the closed-loop attitude control systems of UAV in actuator faulty case. Further, a prescribed transient performance of the FTC attitude control systems is considered which characterizes the convergence rate and maximum overshoot of the attitude tracking error. Finally, simulation results are shown that the attitude control system states remain bounded and the output tracking errors converge to a neighborhood of zero.     

Adaptive compensation for infinite number of actuator failures or faults

It is both theoretically and practically important to investigate the problem of accommodating infinite number of actuator failures or faults in controlling uncertain systems. However, there is still no result available in developing adaptive controllers to address this problem. In this paper, a new adaptive failure/fault compensation control scheme is proposed for parametric strict feedback nonlinear systems. The techniques of nonlinear damping and parameter projection are employed in the design of controllers and parameter estimators, respectively. It is proved that the boundedness of all closed-loop signals can still be ensured in the case with infinite number of failures or faults, provided that the time interval between two successive changes of failure/fault pattern is bounded below by an arbitrary positive number. The performance of the tracking error in the mean square sense with respect to the frequency of failure/fault pattern changes is also established. Moreover, asymptotic tracking can be achieved when the total number of failures and faults is finite.     

Adaptive decentralized fault‐tolerant tracking control for large‐scale nonlinear systems with input quantization

In this paper, an adaptive decentralized tracking control scheme is designed for large‐scale nonlinear systems with input quantization, actuator faults, and external disturbance. The nonlinearities, time‐varying actuator faults, and disturbance are assumed to exist unknown upper and lower bounds. Then, an adaptive decentralized fault‐tolerant tracking control method is designed without using backstepping technique and neural networks. In the proposed control scheme, adaptive mechanisms are used to compensate the effects of unknown nonlinearities, input quantization, actuator faults, and disturbance. The designed adaptive control strategy can guarantee that all the signals of each subsystem are bounded and the tracking errors of all subsystems converge asymptotically to zero. Finally, simulation results are provided to illustrate the effectiveness of the designed approach.     

Adaptive fault‐tolerant control for feedback linearizable systems with an aircraft application

This paper investigates fault‐tolerant control (FTC) for feedback linearizable systems (FLSs) and its applications. The dynamic effects caused by the actuator faults on the feedback linearized model are firstly analyzed, which reveals that under actuator faults, the control input in the linearized model is affected by uncertain terms. In the framework of model reference control, the first FTC strategy is proposed as a robust controller, which achieves asymptotic tracking control of the FLS under actuator faults. A disadvantage of this strategy is that it relies on explicit information about several parameters in the actuator faults. This requirement is later relaxed by combining the robust FTC strategy with an adaptive technique to generate the adaptive FTC law, which is then improved to alleviate possible chattering of the actuator and estimation drifting of the adaptive parameter. Finally, the proposed FTC strategies are evaluated by reference command tracking control of a pendulum and an air‐breathing hypersonic vehicle under actuator faults. Simulation results demonstrate good tracking performance, which confirms effectiveness of the proposed strategies. Copyright © 2014 John Wiley & Sons, Ltd.     

Retrofit fault‐tolerant tracking control design of an unmanned quadrotor helicopter considering actuator dynamics

This paper presents a retrofit fault‐tolerant tracking control (FTTC) design method with application to an unmanned quadrotor helicopter (UQH). The proposed retrofit fault‐tolerant tracking controller is developed to accommodate loss‐of‐effectiveness faults in the actuators of UQH. First, a state feedback tracking controller acting as the normal controller is designed to guarantee the stability and satisfactory performance of UQH in the absence of actuator faults, while actuator dynamics of UQH are also considered in the controller design. Then, a retrofit control mechanism with integration of an adaptive fault estimator and an adaptive fault compensator is devised against the adverse effects of actuator faults. Next, the proposed retrofit FTTC strategy, which is synthesized by the normal controller and an additional reconfigurable fault compensating mechanism, takes over the control of the faulty UQH to asymptotically stabilize the closed‐loop system with an acceptable performance degradation in the presence of actuator faults. Finally, both numerical simulations and practical experiments are conducted in order to demonstrate the effectiveness of the proposed FTTC methodology on the asymptotic convergence of tracking error for several combinations of loss‐of‐effectiveness faults in actuators.     

Adaptive output rejection of unmatched input disturbances

To adaptively reject the effect of certain unmatched input disturbances on the output of a linear time-invariant system, a transfer function matching condition is needed. A lemma which presents a novel basic property of linear systems is derived to characterize system conditions for such transfer function matching. An adaptive disturbance rejection control scheme is developed for such systems with uncertain dynamics parameters and disturbance parameters. This adaptive control technique is applicable to control of systems with actuator failures whose failure values, failure time instants, and failure patterns are unknown. A solution is presented to this adaptive actuator failure compensation problem, which ensures closed-loop stability and asymptotic output tracking, in the presence of any up to m−1 uncertain failures of the total m actuators. Desired adaptive system performance is verified by simulation results.     

Cooperative control for consensus of multi-agent systems with actuator faults

Consensus tracking problem in multi-agent systems with both outage and partial loss of effectiveness types of actuator faults is investigated in this paper. By adopting the virtual actuator technique based on the obtained fault estimates, the effects of possible actuator faults can be effectively compensated in each individual agent. Based on this, a distributed control strategy is developed by using locally available information. It is shown that the tracking error of each fault-free agent can converge to zero and the tracking errors of the faulty agents can remain bounded if the fault estimates are accurate. Moreover, a sufficient condition for achieving bounded tracking errors for all the followers is derived in terms of the fault estimation error. The sliding mode observer is utilized to estimate the faults. Simulation results are given to show the effectiveness of the proposed approach.     

Robust adaptive fault‐tolerant tracking control for a class of high‐order nonlinear system with finite‐time prescribed performance

In this article, an improved prescribed performance adaptive control strategy is developed to handle the output tracking control problem for a class of nonlinear high‐order systems with actuator faults. The actuator faults considered include the bias fault and gain fault models. A technique of adding a power integrator is utilized to deal with the controller design problem of high‐order system. With the help of backstepping technology and the classic adaptive control, an output tracking control scheme is proposed, which can guarantee that all signals of the closed‐loop system are bounded and the tracking error converges to a finite‐time predetermined region. Finally, the feasibility of the presented control method is tested through the simulation results.     

Adaptive fault tolerant control for a class of uncertain fractional‐order systems based on disturbance observer

In this paper, a class of fractional‐order nonlinear systems are considered in the presence of actuator faults. A novel fault tolerant control scheme based on disturbance observer has been presented, where the actuator faults are considered as the system disturbance and can be approximated by the proposed disturbance observer. The developed fault tolerant control guarantees the convergence of the closed‐loop system and the output tracking performance. Finally, a simulation example is presented to verify the effectiveness of the new method.     

Generalized predictive control of linear systems with actuator arrearage faults

Arrearage phenomenon commonly exists in actuators. With arrearages, the actuator cannot achieve the target suggested by the controller, so the control performance degrades. Deadzones and stuck faults can be considered to be two special classes of arrearages, which are studied widely; however, more general arrearage phenomenon cannot be described and treated by these forms. In this paper, a general formulation is introduced for this phenomenon, which is referred as actuator arrearage faults. Based on this formulation, an improved generalized predictive control scheme is proposed for a class of single-input single-output linear systems. With arrearage faults, the system becomes a stochastic process. Hence, a sufficient condition, which guarantees the output tracking error to be uniformly ultimately bounded in the mean-square sense, is presented in this paper. Simulations are given to illustrate the feasibility and effectiveness of the proposed scheme.     

Robust H ∞ and adaptive tracking control against actuator faults with a linearised aircraft application

This article studies the problem of designing adaptive fault-tolerant H _∞ tracking controllers for a class of aircraft flight systems against general actuator faults and bounded perturbations. A robust adaptive state-feedback controller is constructed by a stabilising controller gain and an adaptive control gain function. Using mode-dependent Lyapunov functions, linear matrix inequality-based conditions are developed to find the controller gain such that disturbance attenuation performance is optimised. Adaptive control schemes are proposed to estimate the unknown controller parameters on-line for unparametrisable stuck faults and perturbation compensations. Based on Lyapunov stability theory, it is shown that the resulting closed-loop systems can guarantee asymptotic tracking with H _∞ performances in the presence of faults on actuators and perturbations. An application to a decoupled linearised dynamic aircraft system and its simulation results are given.     

Data-based Fault Tolerant Control for Affine Nonlinear Systems Through Particle Swarm Optimized Neural Networks

In this paper, a data-based fault tolerant control (FTC) scheme is investigated for unknown continuous-time (CT) affine nonlinear systems with actuator faults. First, a neural network (NN) identifier based on particle swarm optimization (PSO) is constructed to model the unknown system dynamics. By utilizing the estimated system states, the particle swarm optimized critic neural network (PSOCNN) is employed to solve the Hamilton-Jacobi-Bellman equation (HJBE) more efficiently. Then, a data-based FTC scheme, which consists of the NN identifier and the fault compensator, is proposed to achieve actuator fault tolerance. The stability of the closed-loop system under actuator faults is guaranteed by the Lyapunov stability theorem. Finally, simulations are provided to demonstrate the effectiveness of the developed method.      

Observer‐Based Adaptive Output Feedback Fault Tolerant Control for Nonlinear Hydro‐Turbine Governing System with State Delay

This paper focuses on the problem of adaptive output feedback fault tolerant control for a nonlinear hydro‐turbine governing system. A dynamic mathematical model of the system is established, which aims to investigate the dynamic performance of the model under servomotor delay and actuator faults. Then, a fault estimation adaptive observer is proposed to achieve online real‐time diagnosis of system faults. Based on the online fault estimation information, an observer‐based adaptive output feedback fault tolerant controller is designed. Furthermore, under reasonable assumptions, the results demonstrate that the closed‐loop control system can achieve global asymptotic stability by Lyapunov function. Finally, the numerical simulation results are presented to indicate the satisfaction control effectiveness of the proposed scheme.     

Adaptive fault tolerant control for a class of input and state constrained MIMO nonlinear systems

In this work, we present a novel adaptive fault tolerant control (FTC) scheme for a class of control input and system state constrained multi‐input multi‐output (MIMO) nonlinear systems with both multiplicative and additive actuator faults. The input constraints can be asymmetric, and the state constraints can be time‐varying. A novel tan‐type time‐varying Barrier Lyapunov Function (BLF) is proposed to deal with the state constraints, and an auxiliary system is designed to analyze the effect of the input constraints. We show that under the proposed adaptive FTC scheme, exponential convergence of the output tracking error into a small neighbourhood of zero is guaranteed, while the constraints on the system state will not be violated during operation. Estimation errors for actuator faults are bounded in the closed loop. An illustrative example on a two degree‐of‐freedom robotic manipulator is presented to demonstrate the effectiveness of the proposed FTC scheme. Copyright © 2015 John Wiley & Sons, Ltd.     

Event-Triggered Bipartite Consensus Tracking and Vibration Control of Flexible Timoshenko Manipulators Under Time-Varying Actuator Faults

For bipartite angle consensus tracking and vibration suppression of multiple Timoshenko manipulator systems with time-varying actuator faults, parameter and modeling uncertainties, and unknown disturbances, a novel distributed boundary event-triggered control strategy is proposed in this work. In contrast to the earlier findings, time-varying consensus tracking and actuator defects are taken into account simultaneously. In addition, the constructed event-triggered control mechanism can achieve a more flexible design because it is not required to satisfy the input-to-state condition. To achieve the control objectives, some new integral control variables are given by using back-stepping technique and boundary control. Moreover, adaptive neural networks are applied to estimate system uncertainties. With the proposed event-triggered scheme, control inputs can reduce unnecessary updates. Besides, tracking errors and vibration states of the closed-looped network can be exponentially convergent into some small fields, and Zeno behaviors can be excluded. At last, some simulation examples are given to state the effectiveness of the control algorithms.

     

A Learning-Based Fault Tolerant Tracking Control of an Unmanned Quadrotor Helicopter

This paper presents a novel learning-based fault tolerant tracking control approach by using an extended Kalman filter (EKF) to optimize a Mamdani fuzzy state-feedback tracking controller. First, a robust state-feedback tracking controller is designed as the baseline controller to guarantee the expected system performance in the fault-free condition. Then, the EKF is employed to regulate the shape of membership functions and rules of fuzzy controller to adapt with the working conditions automatically after the occurrence of actuator faults. Next, based on the modified fuzzy membership functions and rules, the baseline controller is readjusted to properly compensate the adverse effects of actuator faults and asymptotically stabilize the closed-loop system. Finally, in order to verify the effectiveness of the proposed method, several groups of numerical simulations are carried out by comparing the performance of a tracking control scheme and the presented technique. Simulation results demonstrate that the proposed method is effective for optimizing the fuzzy tracking controller on-line and counteracting the side effects of actuator faults, and the control performance is significantly improved as well.     

A Novel Robust Attitude Control for Quadrotor Aircraft Subject to Actuator Faults and Wind Gusts

A novel robust fault tolerant controller is developed for the problem of attitude control of a quadrotor aircraft in the presence of actuator faults and wind gusts in this paper. Firstly, a dynamical system of the quadrotor taking into account aerodynamical effects induced by lateral wind and actuator faults is considered using the Newton-Euler approach. Then, based on active disturbance rejection control (ADRC), the fault tolerant controller is proposed to recover faulty system and reject perturbations. The developed controller takes wind gusts, actuator faults and measurement noises as total perturbations which are estimated by improved extended state observer (ESO) and compensated by nonlinear feedback control law. So, the developed robust fault tolerant controller can successfully accomplish the tracking of the desired output values. Finally, some simulation studies are given to illustrate the effectiveness of fault recovery of the proposed scheme and also its ability to attenuate external disturbances that are introduced from environmental causes such as wind gusts and measurement noises.      

Adaptive type-2 fuzzy sliding mode controller for SISO nonlinear systems subject to actuator faults

In this paper, an adaptive type-2 fuzzy sliding mode control to tolerate actuator faults of unknown nonlinear systems with external disturbances is presented. Based on a redundant actuation structure, a novel type-2 adaptive fuzzy fault tolerant control scheme is proposed using sliding mode control. Two adaptive type-2 fuzzy logic systems are used to approximate the unknown functions, whose adaptation laws are deduced from the stability analysis. The proposed approach allows to ensure good tracking performance despite the presence of actuator failures and external disturbances, as illustrated through a simulation example.     

Prescribed performance adaptive fault tolerant control approach for nonlinear large-scale systems with time delay interconnection and dead zone input

In this study, a prescribed performance adaptive fault tolerant tracking control scheme is presented for a class of nonlinear large-scale systems with time delay interconnection, dead zone input, and actuator fault. The radial basis function neural networks are used to approximate unknown nonlinear functions. Different from the barrier Lyapunov functions used to achieve the symmetrical prescribed performance, a new error transformation is introduced in this study to achieve the desired asymmetrical prescribed performance. In addition, Nussbaum function is introduced to solve the difficulties caused by dead zone input and actuator fault. Based on the appropriate Lyapunov–Krasovskii functions, the effect of time delay interconnection could be compensated. By using backstepping procedures, an adaptive fault tolerant tracking control approach is developed for the considered large-scale systems, and the stability of the closed-loop systems is analyzed by Lyapunov theory. Meanwhile, the prescribed performance of the tracking error could be guaranteed. Finally, the effectiveness of the proposed control approach is illustrated by two simulation examples.