Output Feedback Fault-tolerant Control Research Articles

Output feedback fault-tolerant Q-learning for discrete-time linear systems with actuator faults

This paper presents an innovative output feedback fault-tolerant Q-learning algorithm that can be implemented online without relying on explicit system models or fault details. In the face of actuator faults, finding optimal Fault-Tolerant Control (FTC) solutions that can stabilize the faulty system poses significant challenges. The proposed approach is implemented online without the need for system dynamics and actuator fault information. Furthermore, it operates without relying on full state measurements, utilizing only the input-output data of the faulty system. An innovative representation of the output feedback Fault-Tolerant Q-function (FTQF) is established using input-output data. Subsequently, a model-free optimal output feedback FTC policy is obtained from the developed FTQF. Then, a fault-tolerant Q-learning algorithm is formulated to iteratively acquire the optimal FTC policy in real-time, eliminating the necessity for system dynamics and actuator fault information. The proposed algorithm exhibits immunity to excitation noise bias, even without considering a discounting factor. Furthermore, the proposed Q-learning approach is proven to be effective in stabilizing faulty closed-loop system. Finally, the proposed algorithm's efficiency is validated through numerical simulations of F-16 autopilot aircraft dynamics.

Finite-time output-feedback fault tolerant adaptive fuzzy control framework for a class of MIMO saturated nonlinear systems

This paper presents a finite-time fault-tolerant fuzzy adaptive controller for uncertain interconnected nonlinear systems in strict-feedback form. The controller addresses input saturation, state-dependent actuator faults, external disturbances, and unavailable states for measurement. To avoid any unexpected alteration due to failures, the proposed control scheme design addresses all types of actuator faults that are bias, drift, and loss of accuracy as additive faults, as well as a multiplicative fault that results in loss of effectiveness with nonaffine state-dependency. Restrictions on control gains and unmatched interconnections are eliminated, and the explosion complexity caused by recursive back-stepping designs is avoided. Fuzzy Systems approximate the unknown ideal control laws along side the acutator faults and disturbances. The stability analysis guarantees that tracking errors converge to a small compact set around the origin in finite time. Simulation results on a quad-rotor UAV and a mathematical system confirm the effectiveness of the proposed approach.

Adaptive Fuzzy Finite-Time Output Feedback Fault-Tolerant Control of Stochastic Non-Strict Feedback Nonlinear Systems with Input Saturation and Unknown Control Direction

Adaptive Fuzzy Finite-Time Output Feedback Fault-Tolerant Control of Stochastic Non-Strict Feedback Nonlinear Systems with Input Saturation and Unknown Control Direction

Dynamic output feedback based fault tolerant control for continuous-time switched affine systems via reduced-order observer

In this study, the issue on dynamic output feedback fault-tolerant controller design is addressed for a class of continuous-time switched affine systems in the presence of actuator faults. The existence of affine terms gives rise to the lack of a common equilibrium point and further makes it more difficult to propose the desired output-feedback-based fault-tolerant control scheme. Firstly, the actuator fault estimation is achieved through a reduced-order observer design approach. Then, a kind of dynamic output feedback controller is constructed to perform the fault tolerance goal by utilizing fault estimation information. Moreover, the mode-dependent average dwell time switching constraint is borrowed to avoid the chattering owing to the high-frequency switching. The sufficient conditions with less conservative are derived to guarantee the practical exponential stability of closed-loop system with a prescribed L∞ gain. Finally, both the effectiveness and validity of the designed fault-tolerant control strategy are illustrated via a case study of a buck-boost DC-DC converter.

Integral Sliding Mode Output Feedback Control for Unmanned Marine Vehicles Using T–S Fuzzy Model with Unknown Premise Variables and Actuator Faults

This paper addresses integral sliding mode output feedback fault-tolerant control (FTC) of unmanned marine vessels (UMVs) with unknown premise variables and actuator faults. Due to the complexity of the marine environment, the presence of uncertainties in the yaw angle renders the premise variables in the Takagi–Sugeno (T–S) fuzzy model of UMVs unknown. Consequently, traditional integral sliding mode techniques become infeasible. To address this issue, a control strategy combining integral sliding mode based on output feedback with a compensator utilizing switching mechanisms is proposed. First, a radial basis function neural network is used to approximate the nonlinear terms in the UMV T–S fuzzy model. In addition, an integral sliding mode surface is constructed based on fault estimation information and membership function estimation. On this basis, an FTC scheme based on integral sliding mode output feedback is developed to ensure that the UMV system is asymptotically stable and satisfies the prescribed H∞ performance index. Finally, simulation results are provided to demonstrate the effectiveness of the presented control strategy.

Adaptive fuzzy finite-time output feedback fault-tolerant control for MIMO stochastic nonlinear systems with non-affine nonlinear faults

This paper investigates adaptive fuzzy finite-time output feedback fault-tolerant tracking control problem for multiple-input multiple-output (MIMO) stochastic non-strict feedback nonlinear systems with non-affine nonlinear faults and states unmeasured. Firstly, high-gain fuzzy state observers are constructed to overcome the state unmeasured problem in the system. Secondly, the mean-value theorem and input compensation techniques are employed to decouple non-affine nonlinear faults, and the resulting unknown control coefficients problem is handled using Nussbaum functions. In addition, dynamic surface control techniques and error compensation mechanisms are considered in the controller design, which effectively decreases the computational complexity of the control scheme. By combining the adaptive backstepping technique with finite-time control, a novel adaptive fuzzy dynamic surface finite-time output feedback fault-tolerant tracking control algorithm is proposed. The designed controller guarantees that all signals in the stochastic systems are semi-global finite-time stable in probability (SGFSP) as well as the tracking errors can converge to a small neighborhood within the origin in finite-time. Finally, two simulation examples are introduced to verify the effectiveness of the suggested control strategy.

Dynamic Event-Triggered Output Feedback Fault-Tolerant Control for Dynamic Positioning of Unmanned Surface Vehicles With Multiple Estimators

Dynamic Event-Triggered Output Feedback Fault-Tolerant Control for Dynamic Positioning of Unmanned Surface Vehicles With Multiple Estimators

Two-dimensional model-free Q-learning-based output feedback fault-tolerant control for batch processes

For batch processes with partial actuator failures and unknown system dynamics, an innovative two-dimensional (2D) model-free Q-learning algorithm is proposed to obtain the optimal controller's gains, achieving output feedback fault-tolerant control. First, a 2D linear model is constructed to describe batch processes with partial actuator failures. Then, the state increments in the batch direction and the output errors in the time direction are used as novel state variables to construct a multi-degree-of-freedom model. Second, a 2D Bellman equation is proposed through a connection between a 2D value and a 2D Q functions. Next, a 2D off-policy model-free Q-learning algorithm is highlighted, which incorporates target policies into a multi-degree-of-freedom model and focuses on using policy iteration to solve the fault-tolerant tracking control problem. The robustness analysis rigorously proves the stability of the closed-loop system. Lastly, the simulation results of the holding stage prove the feasibility and effectiveness of the presented algorithm.

Multiple Filters-based Output Feedback Fault-tolerant Control for a Class of Uncertain Nonlinear Systems With Event-triggered Mechanism

Multiple Filters-based Output Feedback Fault-tolerant Control for a Class of Uncertain Nonlinear Systems With Event-triggered Mechanism

Adaptive Fuzzy Output Feedback Fault-Tolerant Control for Active Suspension Systems

In this paper, a novel adaptive fuzzy output feedback fault-tolerant control (FTC) method is proposed for active suspension systems. The quarter active suspension systems studied in this paper contains electromagnetic actuator faults and unavailable state variables, such as the velocity of active suspensions and the electric current intensity of electromagnetic actuators. First, the complex spring nonlinear dynamics are approximated by fuzzy logic systems (FLSs), and the unmeasurable states are estimated by a fuzzy state observer. Based on an adaptive backstepping technique along with specific Lyapunov functions, a novel adaptive fuzzy output feedback FTC design is presented. To eliminate the need for knowing efficiency indexes, a fault compensation strategy is also developed by utilizing parameter estimation technique. In the presence of electromagnetic actuator failure, all vertical vibration states of the active suspension system remain stabilized. Eventually, the feasibility of the proposed control algorithm is evaluated through random road surface and bump road surface tests.

Robust predictive fault-tolerant switching control for discrete linear systems with actuator random failures

Under the condition that state variables are unavailable, a robust predictive fault-tolerant switching control method is proposed for discrete linear systems with actuator random failures. The randomness of failures is described in terms of conditional probabilities. Then, a transfer probability matrix is established to predict the probability of state change. A model incorporating the system state deviation and tracking error is further developed to enhance the regulation of the controller. By using related theories, sufficient conditions for the stability of the system are obtained. Furthermore, average dwell times for the system are obtained according to exponential stability analysis. These times and the matrix form conditions for the output feedback fault-tolerant switching controller to switch between conventional control and fault-tolerant control. Based on the previous work, the research on disturbances and set-point changes has been extended. The feasibility of the method is verified by a case study of the pressure-holding phase.

Fault-Tolerant Fuzzy Observer-Based Fixed-Time Tracking Control for Nonlinear Switched Systems

This paper focuses on developing an adaptive output feedback fault-tolerant fixed-time tracking control strategy for a class of switched nonlinear systems with non-affine faults. To approximate the unmeasurable states, a mode-dependent state switched fuzzy observer is generated using fuzzy logic systems and a Butterworth low-pass filter. Next, an adaptive fixed-time tracking control strategy is developed by combining dynamic surface technology with the backstepping method. An improved mode-dependent average dwell time switching rule is also introduced to ensure the stability of switched nonlinear systems with unstable subsystems. A stability analysis proves the effectiveness of the proposed control scheme in stabilizing the switched nonlinear system under mode-dependent average dwell time switching, ensuring that the tracking error reaches the residual set within a derived settling time. Finally, a switched resistor-inductor-capacitor circuit example is provided to demon- strate the validity of the proposed strategy.

Robust Fault Estimation and Tolerant Control for Uncertain Takagi–Sugeno Fuzzy Systems

This research addresses the intricate challenges of fault estimation (FE) and fault-tolerant control (FTC) within a specific subset of T-S fuzzy systems. These systems are characterized by their localized nonlinear models, the presence of unknown inputs, actuator imperfections, and disruptive output disturbances, making them fertile ground for exploration in this study. The contributions of this paper can be summarized as follows: (1) First, we employ coordinate transformation matrices to convert the T-S fuzzy model. This transformation separates the unknown inputs and disturbances at the output. Subsequently, we equip the modified system with a T-S fuzzy adaptive sliding mode observer (ASMO) that serves the dual purpose of fortifying resilience against disruptions and adeptly deducing an extensive spectrum of fluctuating actuator failure signals. (2) In the next step, the insights gained from FE are harnessed to craft a dynamic fuzzy output feedback fault-tolerant controller (DOFFTC). This controller aims to mitigate the effects of actuator errors to maintain the stability of the closed-loop system. The article creates the necessary conditions for the presence of the required ASMO and DOFFTC using H-infinity filtering methods. To address the optimization issue posed by these criteria, we utilize linear matrix inequalities (LMIs) and calculate the required gains for implementation using convex optimization techniques. (3) The study concludes by illustrating the applicability of the proposed techniques with an example employing an inverted pendulum. This paper presents a comprehensive approach to overcoming the challenges of FE and FTC within T-S fuzzy systems. It leverages precise mathematical formulations and optimization strategies to achieve resilient and dependable control, even when confronted with intricate system dynamics.

ADP based output-feedback fault-tolerant tracking control for underactuated AUV with actuators faults

In this work, the output-feedback fault-tolerant tacking control issue for underactuated autonomous underwater vehicle (AUV) with actuators faults is investigated. Firstly, an output-feedback error tacking system is constructed based on the theoretical model of underactuated AUV with actuators faults. Then, an adaptive dynamic programming (ADP) based fault-tolerant control controller is developed. In our proposed control scheme, a neural-network observer is designed to approximate the system states with actuators faults. An online policy iteration algorithm is designed with critic network and action network in order to improve the tracking accuracy. Based on Lyapunov stability theorem, the stability of the error tracking system is guaranteed by the proposed controller. At last, the simulation results show that the underactuated AUV achieves better tracking performance.

Adaptive dynamic output feedback FTC for nonlinear systems with unknown nonlinearities and faults

AbstractThe problem of adaptive dynamic output feedback fault tolerant control (FTC) for a class of nonlinear systems with unknown nonlinearities and faults is investigated, in which the nonlinearities do not need to satisfy the Lipschitz condition, so the system can represent a wider range of nonlinear system models. An adaptive dynamic output feedback FTC is designed, where the output and its derivatives are fully applied to compensate the actuator faults on systems. The designed control method can effectively offset the effect of faults on systems so as to stabilized the nonlinear system. Furthermore, based on the designed controller, the coupling term can be eliminated reasonably and less conservative stability conditions for the closed‐loop system have been obtained. The proposed control strategy pledges that the states of the closed‐loop system are uniformly ultimately bounded (UUB). Two numerical examples are presented to exhibit the effectiveness and merits of the proposed control scheme.

Formula omitted]output feedback fault-tolerant control of industrial processes based on zero-sum games and off-policy Q-learning

Traditional model-based control methods are often not applicable in industrial processes given the typical situation that model parameters are unknown, coefficient matrices are difficult to obtain, and system states are unpredictable. Accordingly, an output feedback fault-tolerant control method based on zero-sum game theory and off-policy Q-learning is presented in this study, with the aim of achieving smooth operation and good tracking performance for industrial processes that often contain sensor faults and disturbances. The specific steps are as follows. First, a system tracking error is introduced into the system to realize a novel extended model. Second, by establishing a performance index function and combining it with minimax theory, the fault-tolerant tracking control problem is converted into a zero-sum game problem. The Bellman and Riccati equations can be established after analyzing the relationship between the performance index and value functions. Then, the Q-function is introduced, and an off-policy Q-learning algorithm is combined with the Kronecker product without knowledge of system model parameters to design an optimal controller unbiased to detection noise. Finally, the effectiveness of the algorithm is verified by considering the injection molding process as an example. The experimental results validate that the designed controller demonstrates good control and extends the range of tolerable faults while maintaining good tracking performance.

Adaptive output feedback attitude control for reusable launch vehicle with input constraints and actuator faults

This paper considers an adaptive output feedback fault tolerant control (FTC) for a reusable launch vehicle (RLV) during reentry phase for which four grid fins are used as actuators. Based on a prescribed tracking performance and an auxiliary system to deal with the input constraints, the proposed adaptive controller can compensate for the effect of uncertainties, external and internal disturbances, input constraints and actuator faults. It is shown that with the proposed scheme, the system tracking performance can be guaranteed even in the presence multiple actuator faults. The influence of the input constraints on the tracking performance is also investigated. Simulation results are presented to illustrate the effectiveness of the proposed scheme.

Dynamic Output Feedback Fault Tolerant Control for Switched Fuzzy Systems With Fast Time Varying and Unbounded Faults

This paper focuses on the fault reconstruction and fault-tolerant control problems of switched fuzzy systems with actuator and sensor faults, where the faults may be fast time-varying and unbounded. The multiple coordinate transformations are introduced, then the reduced-order observer based fault reconstruction method is considered, which can reconstruct the system state, actuator and sensor faults, simultaneously. For the case that there is no disturbance, the LMI conditions are achieved to insure that for any switching signal, the error dynamics can be exponentially stable. Utilizing the estimated fault information, the fuzzy dynamic output feedback fault tolerant controllers are designed to compensate the fault effect and stabilize the systems. The root-mean-square gain is considered to reduce the disturbance influence on fault estimation and fault-tolerant control, in which the zero initial condition is not needed. Finally, simulations are conducted to demonstrate the effectiveness of the considered techniques.

Analysis and design of control systems via parameter‐based approach

Analysis and design of control systems via parameter‐based approach

Robust saturated fault-tolerant control for active suspension system via partial measurement information

This paper proposes a robust output feedback-fault tolerant control approach associated with the vibration suppression problem for active suspension subject to actuator fault and saturation, unavailable velocity signals, model uncertainty and external disturbance simultaneously. In this paper, an auxiliary system is introduced to solve the actuator saturation problem. The actuator fault, model uncertainty and external disturbance are treated as lumped disturbance. A novel estimator with finite-time convergence characteristics is proposed to estimate the unavailable velocity signals and lumped disturbance, and the disturbance compensation-based controller is designed with the reconstructed signals. In the process of controller design, a nominal controller is designed without lumped disturbance, and the nominal controller and finite-time estimator can be designed independently, so the controller gains can be selected flexibly. Rigorous theoretical analysis is carried out to confirm that all states of the closed-loop system are bounded. In the end, some experimental studies are conducted to show that the active suspension can be controlled effectively, and the efficacy and superiority of the designed method are verified.