Output Feedback Fault-tolerant Control Research Articles

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.

Distributed output-feedback resilient fault-tolerant tracking control of uncertain heterogeneous linear MASs under directed topologies and DoS attacks

This paper presents a distributed output-feedback resilient tracking fault-tolerant control (FTC) protocol for uncertain heterogeneous linear multi-agent systems (MASs) with directed topologies and DoS attacks. The uncertainty, actuator fault and nonidenticality in agents and DoS attacks in directed communication topologies, make it a challenging task to achieve distributed output-feedback FTC objective. In order to solve this difficulty, a hierarchical framework is introduced. The basic idea is to design distributed resilient observers under directed topologies and DoS attacks. By virtue of switching systems theory, the upper bounds of attack frequency and attack duration are obtained. Based on neural networks approximation technique and model reference tracking method, a novel output-feedback FTC scheme is proposed. Lastly, simulation example indicates the validity of the proposed method.

Finite-Time Dynamic Event-Triggered Fuzzy Output Fault-Tolerant Control for Interval Type-2 Fuzzy Systems

The finite-time dynamic event-triggered fuzzy output feedback fault-tolerant control problem is studied in this article for the interval type-2 (IT2) Takagi–Sugeno fuzzy system with parameter uncertainties and actuator faults. A fuzzy state observer is first developed to solve the immeasurable state problem. Second, by using the sampled estimating states and measured output signals, a dynamic event-triggered mechanism is formulated via integrating sensor-to-observer with observer-to-controller. Third, an observer-based finite-time event-triggered fuzzy fault-tolerant controller is synthesized via the nonparallel distribution compensation design principle. Consequently, the finite-time stable conditions of the addressed IT2 fuzzy system are established by constructing an appropriate Lyapunov function. Furthermore, an output feedback control design algorithm of solving control and observer gains is given in terms of the established sufficient finite-time stable conditions. Finally, a practical example of a nonlinear tunnel diode circuit system is provided to verify the effectiveness of the proposed IT2 fuzzy control scheme.

Static Output Feedback Fault Tolerant Control and Relaxed Stability Analysis of Positive Polynomial Fuzzy Systems

The increased demand for safety in control systems has motivated the research for fault-tolerant controllers (FTCs). This article presents the static output feedback FTC design and relaxed stability analysis for positive nonlinear systems on account of polynomial fuzzy models. A polynomial copositive Lyapunov function candidate is proposed for the stability analysis of positive polynomial fuzzy-model-based (PPFMB) control systems for the first time. This method develops the decision variable on the polynomial copositive Lyapunov function candidate to be a polynomial vector and also makes it independent of the form of the positive polynomial fuzzy model. Thus, it can be applied to a more extensive range of PPFMB control systems and potentially generates more relaxed stability analysis results. To achieve the stability analysis and control synthesis, the following challenges are overcome: 1) approximate the nonconvex terms in stability and positivity conditions into convex ones through the idea of matrix decomposition; 2) eliminate the nonconvex conditions resulting from the derivative of the polynomial Lyapunov function by employing an sum-of-squares (SOS) optimization method; 3) relax the results of stability analysis and control design by introducing the advanced membership-function-dependent technique to develop both the stability conditions and the positivity conditions. The relaxed conditions are obtained on the basis of SOS form so that the MATLAB third-party toolbox, SOSTOOLS, can be used to find feasible solutions. Finally, two simulation examples are presented to illustrate the effectiveness of the proposed method.

Fuzzy Adaptive Output Feedback Fault-Tolerant Control for Nonlinear Switched Large-Scale Systems With Sensor Faults

To handle the decentralized fuzzy adaptive outputfeedback fault-tolerant control problem for nonlinear switched large-scale systems with sensor faults and unknown control gains, a decentralized fault-tolerant control (FTC) strategy is proposed. As only the actual outputs are measurable when the sensor faults occur, a novel state observer is designed to estimate unmeasured states and address unknown control gains simultaneously. The unknown nonlinear functions are approximated by fuzzy logic systems. Based on the backstepping technique and the average dwell time method, decentralized FTC controllers are designed. It is proven that all states of the closed-loop system are semiglobal uniformly ultimately bounded and the tracking errors can converge to a small neighborhood of zero. A simulation example is presented to show the effectiveness of the developed strategy.

Neural Network-Based Output Feedback Fault Tolerant Tracking Control for Nonlinear Systems with Unknown Control Directions

In this study, an adaptive output feedback fault tolerant control (FTC) scheme is proposed for a class of multi-input and multioutput (MIMO) nonlinear systems with multiple constraints. The neural network (NN) is adopted to handle the unknown nonlinearity by means of its superior approximation capability. Based on it, the state observer is designed to estimate the unmeasured states, and the nonlinear disturbance observer is constructed to tackle the external disturbances. In addition, the Nussbaum function is utilized to cope with the actuator faults, which are coupled with the unknown control directions. Combining with the Lyapunov theory, a NN-based output feedback FTC law is developed for the MIMO nonlinear systems, and the boundedness of all closed-loop system error signals is proved. Simulation results on the unmanned helicopter are performed to demonstrate the effectiveness of the proposed controller.