Optimal Fault-tolerant Control Research Articles

Event‐triggered decentralized optimal fault tolerant control for mismatched interconnected nonlinear systems through adaptive dynamic programming

AbstractIn this paper, we propose an event‐triggered decentralized optimal fault tolerant control (ETDOFTC) scheme based on adaptive dynamic programming for mismatched interconnected nonlinear systems with actuator failures. For fault‐free dynamic models, the decentralized control problem is addressed by developing a set of decentralized optimal control strategies for isolated subsystems with modified value functions, which are approximated by critic neural networks. Meanwhile, the neural network‐based decentralized observer is established to approximate actuator failures and mismatched unknown interconnections. The weights of the neural networks are aperiodically updated at the designed triggering instants. Then, the proposed ETDOFTC scheme is obtained by combining the event‐triggered decentralized optimal control strategies with the adaptive fault compensators. Furthermore, it is proved that all the signals of the closed‐loop system are uniformly ultimately bounded via the Lyapunov stability analysis. Finally, simulation results of two examples are presented to confirm the effectiveness of the proposed ETDOFTC scheme.

Prescribed performance incremental adaptive optimal fault-tolerant control for nonlinear systems with actuator faults

In this paper, a model-free incremental adaptive optimal fault-tolerant controller with prescribed performance is proposed for nonlinear systems subject to actuator faults. Considering the system actuator redundancy, an actuator grouping scheme is introduced according to the actuator functions. An incremental adaptive fault observer is designed to estimate the faults. The recursive least squares (RLS) identification is utilized to identify the incremental system parameters. Both dynamic process requirements and optimal performance index of the closed loop system are taken into consideration by combining prescribed performance bound (PPB) and incremental adaptive dynamic programming (IADP). Simulations are given to verify the effectiveness of the proposed IADP reconfigurable fault-tolerant control scheme.

Policy Iteration Based Online Adaptive Optimal Fault Compensation Control for Spacecraft

In this paper, a novel online adaptive optimal fault-tolerant control (FTC) scheme based on policy iteration (PI) algorithm is developed for the spacecraft attitude angular velocity tracking control with actuator faults. First, for the fault-free attitude dynamic model, an adaptive optimal controller is designed based on PI algorithm to solve the Hamilton-Jacobi-Bellman (HJB) equation. In this process of solving, the value function is approximated by means of a critic neural network (NN). Then, a novel adaptive compensation law is proposed for estimation of actuator faults. The closed-loop system is proved to be uniformly ultimately bounded (UUB) via the Lyapunov’s method. Finally, the effectiveness of the proposed control scheme is evaluated via simulation experiments.

Two-Level Game-Based Distributed Optimal Fault-Tolerant Control for Nonlinear Interconnected Systems.

This article addresses the distributed optimal fault-tolerant control (FTC) issue by using the two-level game approach for a class of nonlinear interconnected systems, in which each subsystem couples with its neighbors through not only the states but also the inputs. At the first level, the FTC problem for each subsystem is formulated as a zero-sum differential game, in which the controller and the fault are regarded as two players with opposite interests. At the second level, the whole interconnected system is formulated as a graphical game, in which each subsystem is a player to achieve the global Nash equilibrium for the overall system. The rigorous proof of the stability of the interconnected system is given by means of the cyclic-small-gain theorem, and the relationship between the local optimality and the global optimality is analyzed. Moreover, based on the adaptive dynamic programming (ADP) technology, a distributed optimal FTC learning scheme is proposed, in which a group of critic neural networks (NNs) are established to approximate the cost functions. Finally, an example is taken to illustrate the efficiency and applicability of the obtained theoretical results.

Actuator Fault Tolerant Control of Variable Pitch Quadrotor Vehicles

Abstract Variable pitch quadrotors can experience actuation faults and failures of two main types: one type related to the rotor system and the other one related to the blade pitch servo. In this paper, we face the fault tolerant attitude tracking problem for a variable pitch quadrotor, in case of partial loss of effectiveness of the rotor system or lock-in-place of the blade pitch servo. The proposed solution is based on the combination of the Disturbance Observer Based Control design paradigm together with that of Active Fault Diagnosis. In detail, an observer is designed for estimating the thrust produced by each rotor. An active diagnosis scheme is adopted to discriminate which fault/failure is affecting the system. Finally, a control allocation algorithm solves the optimal redistribution problem of the control effort among the rotors, subject to different constraints. The proposed overall optimal fault tolerant control scheme can be coupled with most of the nonlinear control laws commonly applied to conventional, fixed pitch, quadrotor systems. Numerical simulations show the capability of the proposed scheme to handle both loss of effectiveness of the rotor system or lock-in-place of the blade pitch servo.

Multiple model-based fault-tolerant control system for distributed drive electric vehicle

Generally, the distributed drive electric vehicle (DDEV) works under different fault status, and this may lead to unstable operating performance. However, the conventional fault-tolerant controller is only suitable for one special fault status, and thus, the stability of DDEV is hard to be guaranteed efficiently. To deal with this problem, a novel multiple model-based fault-tolerant control system (MMFTCS) is proposed in this paper. The MMFTCS integrates an operating status recognizer and a fault-tolerant controller set. The operating status recognizer is designed to distinguish current operating status, where the matching degree between current operating status and typical operating mode set is detected using fuzzy logic. The fault-tolerant controller set is designed to achieve optimal fault-tolerant control, and each fault-tolerant controller is designed for the corresponding typical operating mode by the model predictive controller. The output of the MMFTCS is computed by the weighted signal of each fault-tolerant controller to realize smooth switching. The simulation is carried on the MATLAB environment, and the results show that the MMFTCS has excellent fault-tolerant performance under various operating status.

Offshore Platform Actuator Fault Optimal Anti-Interference Self-Repair Fault-Tolerant Control

Li, F., 2019. Offshore platform actuator fault optimal anti-interference self-repair fault-tolerant control. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 153–156. Coconut Creek (Florida), ISSN 0749-0208.A fault-tolerant control method based on extended fault diagnostics is proposed for the actuator failure of offshore platforms under the influence of ocean waves. Firstly, a self-repairing fault-tolerant control law is designed for actuator failure. Then an optimal anti-interference self-repairing fault-tolerant controller is designed according to Riccati and Sylvester matrix equations to ensure that the offshore platform system is optimal under fault and wave interference. In order to solve the physical unrealizable problem that the system state and faults in fault-tolerant control cannot be directly measured, an extended fault diagnostic device is designed. Finally, numerical simulation results verify the feasibility and effectiveness of this scheme.

Fault-Tolerant Attitude Stabilization Incorporating Closed-Loop Control Allocation Under Actuator Failure

This paper addresses the difficult problem of fault-tolerant control and closed-loop control allocation for spacecraft attitude control system with actuator failures, actuator saturation, and external disturbances. As a fundamental step, a modified fault diagnosis observer is proposed utilizing the iterative learning methodology to reconstruct the actuator failures in real time. On the basis of the previously reconstructed failure information, a fault-tolerant control scheme incorporating with a parameter adjusting law is presented to enforce the spacecraft attitude control system to reach the real sliding mode surface in finite time. Meanwhile, the singularity of control command will be avoided using the saturation function, and the chattering problem restrained by the adjusting law. Furthermore, with the concept of control allocation, a novel on-line closed-loop constrained optimal fault-tolerant control allocation scheme is employed to distribute the signals synthesized by the baseline controller over the redundant actuators with failures and constraints. The stability of the closed-loop fault-tolerant control allocation process is guaranteed by the theory of the closed-loop discrete-time feedback control system. The key achievement of the proposed systematic strategy is that the whole closed-loop attitude control system can theoretically be guaranteed to be stable. Numerical simulations are carried out to verify the effectiveness and superiority of the developed approach.

Fault tolerant cooperative control for affine multi-agent systems: An optimal control approach

The goal of this paper is to propose an optimal fault tolerant control (FTC) approach for multi-agent systems (MASs). It is assumed that the agents have identical affine dynamics. The underlying communication topology is assumed to be a directed graph. The concepts of both inverse optimality and partial stability are further employed for designing the control law fully developed in the paper. Firstly, the optimal FTC problem for linear MASs is formulated and then it is extended to MASs with affine nonlinear dynamics. To solve the Hamilton-Jacobi-Bellman (HJB) equation, an Off-policy Reinforcement Learning is used to learn the optimal control law for each agent. Finally, a couple of numerical examples are provided to demonstrate the effectiveness of the proposed scheme.

Adaptive Fuzzy Robust Fault-Tolerant Optimal Control for Nonlinear Large-Scale Systems

The problem of adaptive fuzzy decentralized fault-tolerant optimal control is investigated for nonlinear large-scale systems with actuator faults in this paper. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions and learn cost functions. Filtered signals are adopted to circumvent the problems of an algebraic loop on designing the decentralized controllers. Based on the backstepping technique and fault-tolerant control technique, a decentralized feedforward control strategy is designed. Based on the adaptive critic technique, a decentralized feedback optimal control strategy is designed. By combining the feedforward control strategy with the feedback optimal control strategy, a novel adaptive fuzzy decentralized fault-tolerant optimal control scheme is established. The stability of the closed-loop system is proved by using the Lyapunov stability theory. The effectiveness of the proposed decentralized control approach is confirmed via a simulation example.

Adaptive optimal fault-tolerant control scheme for a class of strict-feedback nonlinear systems

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.

Optimal Fault-Tolerant Control against Descriptor Time-Varying Systems with Nonlinear Input

The problem of optimal fault-tolerant control for a class of descriptor time-varying systems with nonlinear input is considered. Based on the Lyapunov stability theorem, the sufficient conditions of the stability are obtained when the system is normal and ineffective. Furthermore, the fault-tolerant control of the systems is carried out in two cases, and the state feedback fault-tolerant controller is obtained to satisfy the quadratic performance index and reach the minimum value in order to achieve the optimal fault-tolerant control. Finally, the validity of the proposed approach is illuminated by a numerical example.

Optimal Fault-Tolerant Control for Discrete-Time Nonlinear Strict-Feedback Systems Based on Adaptive Critic Design.

This paper investigates the problem of optimal fault-tolerant control (FTC) for a class of unknown nonlinear discrete-time systems with actuator fault in the framework of adaptive critic design (ACD). A pivotal highlight is the adaptive auxiliary signal of the actuator fault, which is designed to offset the effect of the fault. The considered systems are in strict-feedback forms and involve unknown nonlinear functions, which will result in the causal problem. To solve this problem, the original nonlinear systems are transformed into a novel system by employing the diffeomorphism theory. Besides, the action neural networks (ANNs) are utilized to approximate a predefined unknown function in the backstepping design procedure. Combined the strategic utility function and the ACD technique, a reinforcement learning algorithm is proposed to set up an optimal FTC, in which the critic neural networks (CNNs) provide an approximate structure of the cost function. In this case, it not only guarantees the stability of the systems, but also achieves the optimal control performance as well. In the end, two simulation examples are used to show the effectiveness of the proposed optimal FTC strategy.

Observer-Based Adaptive Fuzzy Fault-Tolerant Optimal Control for SISO Nonlinear Systems.

This paper investigates adaptive fuzzy output feedback fault-tolerant optimal control problem for a class of single-input and single-output nonlinear systems in strict feedback form. The considered nonlinear systems contain unknown nonaffine nonlinear faults and unmeasured states. Fuzzy logic systems are used to approximate cost function and unknown nonlinear functions, respectively. It is assumed that the states of the systems to be controlled are unmeasurable, thus an adaptive state observer is developed. To solve the nonaffine nonlinear fault control design problem, filtered signals are introduced into the adaptive backstepping control design procedures, and in the framework of adaptive critic technique and fault-tolerant control technique, a novel adaptive fuzzy fault-tolerant optimal control scheme is developed. The stability of the closed-loop system is proved by using Lyapunov stability theory. The simulation results verify the effectiveness of the proposed control strategy.

Optimal fault-tolerant control strategy of a solid oxide fuel cell system

For solid oxide fuel cell (SOFC) development, load tracking, heat management, air excess ratio constraint, high efficiency, low cost and fault diagnosis are six key issues. However, no literature studies the control techniques combining optimization and fault diagnosis for the SOFC system. An optimal fault-tolerant control strategy is presented in this paper, which involves four parts: a fault diagnosis module, a switching module, two backup optimizers and a controller loop. The fault diagnosis part is presented to identify the SOFC current fault type, and the switching module is used to select the appropriate backup optimizer based on the diagnosis result. NSGA-II and TOPSIS are employed to design the two backup optimizers under normal and air compressor fault states. PID algorithm is proposed to design the control loop, which includes a power tracking controller, an anode inlet temperature controller, a cathode inlet temperature controller and an air excess ratio controller. The simulation results show the proposed optimal fault-tolerant control method can track the power, temperature and air excess ratio at the desired values, simultaneously achieving the maximum efficiency and the minimum unit cost in the case of SOFC normal and even in the air compressor fault.

Fault diagnosis and fault-tolerant tracking control for discrete-time systems with faults and delays in actuator and measurement

In this paper, the fault diagnosis (FD) and fault-tolerant tracking control (FTTC) problem for a class of discrete-time systems with faults and delays in actuator and measurement is investigated. In the first step, a discrete delay-free transformation approach is introduced for an constructed augmented system such that the two-point-boundary-value (TPBV) problem with advanced and delayed items can be avoided. Then, the optimal fault-tolerant tracking controller (OFTTC) is proposed with respect to an equivalent reformed quadratic performance index. Moreover, by using the real-time system output rather than the residual errors, a reduced-order-observer-based fault diagnoser for the augmented system is designed to diagnose faults in actuator and measurement, and solve the physically unrealizable problem of proposed OFTTC. Finally, the effectiveness of the proposed fault diagnoser and OFTTC is illustrated by a realistic design example for industrial electric heater.

Bi-index Constraints-Based Output Feedback Fault-Tolerant Control for Aero-Engine Distributed Control Systems

With a focus on the aero-engine distributed control system (DCS) with parameter perturbation, Markov time delay, data packet dropout and external disturbance, a research has been carried out on DCS fault-tolerant control on condition of partial failure of actuator. First, a quantitative description of the system parameters is given, and the augmented model of the entire closed-loop system is established. Then the stability of the closed-loop system constrained by \(H_\infty \) and cost performance index is analyzed, and the method of designing optimal guaranteed cost fault-tolerant controller is proposed based on dynamic output feedback. Finally, the consistency theory of bi-index constraints is introduced, based on which the fault-tolerant controller is designed. The simulation results show that the designed controller can effectively reduce the controlling cost of the system while guaranteeing its \(H_\infty \) performance.

Optimal fault-tolerant control for UAV systems with time delay and uncertainties over wireless network

This paper presents an optimal fault-tolerant control scheme for time-delay systems in wireless network. In order to solve the problem of time delay caused by wireless transmission, time delay compensation item is added to the sliding surface to eliminate the impact of state time delay. Aiming at the modeling uncertainties of the systems, sufficient conditions for asymptotic stability of ideal sliding mode of the system are given based on LMI (linear matrix inequality) technique. To deal with the actuator faults, optimal index of quadratic form is designed to optimize the control law of the nominal system, and then the sliding mode switching control law is constructed to complete the optimal fault-tolerant control for time delay systems with the actuator faults. Finally, the proposed method is applied to the wireless network control system of the quad-rotor UAV (Unmanned Aerial Vehicle). The experiment results show that the proposed method in this paper has obvious advantages compared with the traditional method.

Optimal adaptive fuzzy FTC design for strict-feedback nonlinear uncertain systems with actuator faults

In this paper, the optimal fault-tolerant control (FTC) design problem is investigated for strict-feedback nonlinear systems. The considered nonlinear systems contain actuator faults, which are bias fault and gain fault. The problem of actuator faults is solved by utilizing the adaptive compensation technique. Applying the backstepping design technique, a main fault-tolerant controller is established. Via the designed main fault-tolerant control strategy, the controlled nonlinear system can be converted to an equivalent nonlinear system in affine form. Subsequently, a fuzzy logic system (FLS) is introduced to approximate the unknown cost function, and an adaptive fuzzy feedback optimal controller is developed. The whole adaptive fuzzy fault-tolerant optimal control scheme consists of a main controller and a feedback optimal controller. Based on the Lyapunov theory, it is proved that all the signals in the closed-loop system are bounded, the system output can track a bounded reference signal. In addition, the proposed control method can guarantee the cost function is the smallest. Simulation results are provided to illustrate the effectiveness of the proposed fault-tolerant optimal control scheme.

Integrated fault estimation and fault-tolerant control for uncertain Lipschitz nonlinear systems

Summary This paper proposes an integrated fault estimation and fault-tolerant control (FTC) design for Lipschitz non-linear systems subject to uncertainty, disturbance, and actuator/sensor faults. A non-linear unknown input observer without rank requirement is developed to estimate the system state and fault simultaneously, and based on these estimates an adaptive sliding mode FTC system is constructed. The observer and controller gains are obtained together via H∞ optimization with a single-step linear matrix inequality (LMI) formulation so as to achieve overall optimal FTC system design. A single-link manipulator example is given to illustrate the effectiveness of the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd.