Adaptive Fuzzy Fault-tolerant Control Research Articles

Fuzzy Adaptive Fault-tolerant Control for Underactuated Wheeled Mobile Robot With Prescribed Performance

Fuzzy Adaptive Fault-tolerant Control for Underactuated Wheeled Mobile Robot With Prescribed Performance

Integral reinforcement learning–based adaptive fuzzy fault tolerant control of hypersonic flight vehicle

The fault tolerant control (FTC) of hypersonic flight vehicle (HFV) with actuator fault is proposed in this paper. The fault model considered in this paper is a general model which HFV may encounter in practice. For designing the FTC, the nonlinear model of HFV is represented by T-S fuzzy models, and policy iteration (PI) strategy is utilized to solve the design problem of T-S controller for the built T-S model of HFV without actuator fault. Then, based on the normal T-S controller, an adaptive fuzzy FTC controller is proposed, in which the feedback gain matrices can improve themselves according to the special fault. The stability of the proposed adaptive fuzzy FTC is proved by Lyapunov theory, and an integral reinforcement learning (IRL)–based solving algorithm is proposed. Simulations on three different kinds of actuator faults are proposed, and the simulation results show that, under three different faults, the designed adaptive FTC can ensure the reliable flight of HFV.

Event-Triggered Adaptive Fuzzy Fault-Tolerant Attitude Control for Tailless Flying-Wing UAV with Fixed-Time Convergence

Event-Triggered Adaptive Fuzzy Fault-Tolerant Attitude Control for Tailless Flying-Wing UAV with Fixed-Time Convergence

Observer-Based Fuzzy Adaptive Fault-Tolerant Control for NSC System of USV With Sideslip Angle and Steering Machine Fault

Observer-Based Fuzzy Adaptive Fault-Tolerant Control for NSC System of USV With Sideslip Angle and Steering Machine Fault

Optimal adaptive fuzzy fault-tolerant control applied on a quadrotor attitude stabilization based on particle swarm optimization

This article discusses the problem of stabilizing the attitude control of a quadrotor system, which is subject to uncertainty, external disturbances, and sensor and actuator faults. To address these challenges, the control stage employs universal approximators, such as fuzzy systems, which estimate the system’s uncertainties and eliminate nonaffine nonlinear actuator faults. In addition, the particle swarm optimization technique is used to adjust the adaptive parameters and fuzzy initial values. The robust control term is carefully designed to handle approximation errors, time-varying sensors, and external disturbances. To solve the issue of the unavoidable algebraic loop during the actuator approximation phase, a Butterworth low-pass filter is integrated. This approach automatically deals with external disturbances, and no further approximation is necessary. Furthermore, the controller can be reconfigured online to enable fast-fault compensation without requiring a fault detection or isolation unit. To prove the global stability and boundedness of all signals in the closed-loop system, Lyapunov theory is used.

Robust Adaptive Fuzzy Fault Tolerant Control of Robot Manipulators With Unknown Parameters

This paper resolves the safety tracking problem of the robot manipulator with the actuator faults, process faults, uncertain dynamics, and external disturbances. A novel robust adaptive fuzzy fault tolerant control (FTC) framework is presented. In this approach, a constraint mechanism of the zero overshoot error is proposed to keep the filter variable within an adjustable range, and the compact set can be available. An adaptive fuzzy logic system (FLS) is, then, employed to approximate the time-varying, nonlinear, and unknown robot dynamics. Furthermore, a robust adaptive term is designed to compensate the actuator faults and approximation errors, and ensure the convergence and stability of the whole robot control system. The uniform ultimate boundedness of the closed-loop dynamics for the robot manipulator is proved by the Lyapunov function. Afterwards, the simulation results demonstrate that the proposed robust adaptive fuzzy FTC (RAFFTC) approach of the robot manipulator has good control performance. Finally, the effectiveness of the proposed RAFFTC approach is verified by experiments.

Adaptive Fuzzy Fault Tolerant Control for Robot Manipulators With Fixed-Time Convergence

This paper aims to resolve the three major issues of fault tolerant control (FTC) for robot manipulators: (i) the faster response, lower tracking errors, lower chattering and higher robustness of the FTC, (ii) the requirement of partial or full knowledge of robot dynamics for the design of model-based FTC, and (iii) the global fixed-time convergence of the system. First, a fixed-time controller based on a backstepping control is designed and its disadvantages are analysed. Then, an adaptive fuzzy backstepping control is developed to enhance the tracking performance of the system. The proposed approach does not require the full prior knowledge of robot dynamic model, thus facilitating implementation of the controller in practical applications. In addition, the tracking errors of the system will be practically convergent within a fixed-time, which provides additional system information in advance. The fixed time convergence of the system is mathematically proved and the performance of the system is demonstrated for FTC of a PUMA560 robot.

Command-Filtered Finite-Time Fuzzy Adaptive Fault-Tolerant Control of Output-Constrainted Robotic Manipulators With Unknown Dead-Zones

This article presents a barrier Lyapunov functions-based (BLFs) adaptive fuzzy finite-time fault-tolerant control scheme for the manipulator with actuator faults and unknown dead-zones. Firstly, by constructing time-varying BLFs, the system output will be constrained in time-varying regions. Secondly, an adaptive method is designed to estimate the degree of actuator faults and to compensate for the effect of dead-zones. Thirdly, the command filtered backstepping with error compensation mechanism is introduced to approximate the virtual control laws, which can not only solve the “explosion of complexity” problem, but also improve the control accuracy. The control method can ensure that all signals of the closed-loop system are finite-time bounded, the tracking errors of joint positions converge to a small neighborhood of the origin, and meets the requirements of time-varying constraints. Finally, a rigid manipulator is used to verify the effectiveness of the scheme.

General fuzzy adaptive fault-tolerant control based on Nussbaum-type function with additive and multiplicative sensor and state-dependent actuator faults

The present paper devotes to propose a general active fault-tolerant control (GAFTC) for a class of unknown multi-input multi-output (MIMO) nonlinear systems that are subject to simultaneous additive and multiplicative sensor and nonaffine nonlinear state-dependent actuator faults, exogenous disturbances and multiple unknown control directions. By combining fuzzy logic systems and back-stepping technique, an adaptive control unit along with a robust control unit are developed. In the proposed approach, the unknown dynamics along with sensor and non-affine nonlinear state-dependent actuator faults are approximated to avoid developing fault detection and isolation unit. Furthermore, the difficulty caused by the unknown control gain directions is solved by using the Nussbaum-type function. The adaptation mechanism is proposed to overcome fuzzy approximation errors and exogenous disturbances, and the Butterworth low-pass filter is adopted to get rid of the algebraic loop appearing in the actuator faults approximation. The stability of the closed-loop system is proved by Lyapunov method where all the signals involved in the resulting closed-loop system are shown to be bounded, and the tracking errors converge asymptotically to the origin. Quadrotor attitude dynamics stabilization is proposed in the simulation study to test the accuracy and the effectiveness of the proposed control scheme.

Observer-Based Adaptive Fuzzy Quantized Fault-Tolerant Control of Nonstrict-Feedback Nonlinear Systems With Sensor Fault

This paper focuses on the problem of adaptive quantized fault tolerant tracking control for a class of uncertain nonstrict-feedback nonlinear systems in the presence of input and output quantization and sensor fault. The main technical challenges come from how to deal with the input and output quantization errors and the partial loss of sensors' effectiveness. Firstly, a new observer including the quantized input and output signals and the estimation of fault parameter is designed to reconstruct the unavailable states, and some special techniques are developed to deal with the sector-bounded quantization errors. Furthermore, based on the cubic absolute-value Lyapunov function, the adaptive fault compensation strategy is presented to make up for the influence from sensor fault upon the control performance. Then, with the aid of fuzzy logic system (FLS) approximation method and backstepping technique, a novel output feedback adaptive fuzzy fault tolerant control (FTC) scheme is proposed for this class of systems, such that all signals in the closed-loop are semi-globally uniformly ultimately bounded (SGUUB) while the tracking error remains in a small vicinity of the origin. Finally, the effectiveness and applicability of the proposed control scheme are validated by conducting two simulation examples.

Interval Type-II Fuzzy Fault-Tolerant Control for Constrained Uncertain 2-DOF Robotic Multi-Agent Systems with Active Fault Detection

This study proposed a novel adaptive interval Type-II fuzzy fault-tolerant control for constrained uncertain 2-DOF robotic multi-agent systems with an active fault-detection algorithm. This control method can realize the predefined-accuracy stability of multi-agent systems under input saturation constraint, complex actuator failure and high-order uncertainties. Firstly, a novel active fault-detection algorithm based on pulse-wave function was proposed to detect the failure time of multi-agent systems. To the best of our knowledge, this was the first time that an active fault-detection strategy had been used in multi-agent systems. Then, a switching strategy based on active fault detection was presented to design the active fault-tolerant control algorithm of the multi-agent system. In the end, based on the interval type-II fuzzy approximated system, a novel adaptive fuzzy fault-tolerant controller was proposed for multi-agent systems to deal with system uncertainties and redundant control inputs. Compared with other relevant fault-detection and fault-tolerant control methods, the proposed method can achieve predefinition of stable accuracy with smoother control input. The theoretical result was verified by simulation.

Finite-Time Adaptive Fuzzy Control for Unmodeled Dynamical Systems with Actuator Faults

This article concentrates upon the issue of finite-time tracking control for a category of nonlinear systems in pure-feedback form with actuator faults and unmodeled dynamics, where the loss of effectiveness and bias fault are considered. Meanwhile, the function approximation method utilizing fuzzy logic systems and dynamic surface control approach with first-order filter are implemented to model the unknown nonlinear terms induced from the proposed controller procedure and tackle the “explosion of complexity” issue of the classic backstepping method. The use of the maximal norm of the weight vector estimation method and adaptive approach reduces the computation load induced by fuzzy logic systems. Within the framework of backstepping control, a finite-time adaptive fuzzy fault-tolerant control protocol is derived to guarantee the boundedness of all signals and tracking error of the controlled system within a finite-time. Simulation studies are offered to show the validity of the derived theoretical results of the finite-time control protocol.

Adaptive Output Feedback Fuzzy Fault-Tolerant Control for Nonlinear Full-State-Constrained Switched Systems.

In this article, an output feedback adaptive fuzzy tracking control method for a class of switched uncertain nonlinear systems with actuator failures and full-state constraints is proposed under an arbitrary switching signal combining the dynamic surface technique. Since the state variables of the system under study are not measurable, a fuzzy observer is constructed to identify the unmeasured states. The actuator failures are considered in the system. To compensate this failure, a fault-tolerant controller is proposed. Moreover, each state needs to be kept within the constraints, so the tangent Barrier Lyapunov function is selected to solve the full-state constraint problem, and the unknown nonlinear function is approximated by fuzzy-logic systems (FLSs). We also proved that all signals in the closed-loop system are bounded. Furthermore, the states can be kept within the predetermined range even if the actuator fails. Finally, a simulation example is given to verify the effectiveness of the proposed control strategy.

Distributed adaptive fuzzy fault-tolerant control for multi-agent systems with node faults and denial-of-service attacks

This paper studies the distributed adaptive fuzzy fault-tolerant control for multi-agent systems (MASs) with node faults and denial-of-service (DoS) attacks. On account of DoS attacks, the fixed network topology is changed into switching topologies, which brings about many difficulties in designing fault-tolerant controllers. In addition, node faults and nonlinearity terms make it more challenging to analyze the stability of MASs with DoS attacks. To cope with the nonlinear terms in MASs, a fuzzy logic systems method is provided. Also, based on the switching mechanism, the average dwell time technique, and the Lyapunov stability theory, a distributed adaptive fuzzy fault-tolerant controller is proposed, and the bounded synchronization of the MASs is achieved. A simulation example is used to validate the efficiency of the proposed approach.

Disturbance Observer-based Adaptive Fuzzy Fault-tolerant Tracking Control for Uncertain Nonlinear Systems with Input Delay and Actuator Faults

Disturbance Observer-based Adaptive Fuzzy Fault-tolerant Tracking Control for Uncertain Nonlinear Systems with Input Delay and Actuator Faults

Adaptive fuzzy fault-tolerant control for active seat suspension systems with full-state constraints

In this paper, an adaptive fuzzy fault-tolerant control (FTC) scheme is proposed for active seat suspension systems. The addressed system contains electromagnetic actuator faults. In addition, the constraints of the displacements of the car seat, active suspension, and wheel, their vertical vibration speeds and current intensity are included. In the control design, since the systems have dynamic characteristics of complexities and spring non-linearities, the fuzzy logic systems are utilized to approximate the unknown nonlinear dynamics. By the aid of Barrier Lyapunov functions and based on the adaptive backstepping recursive design algorithm, a novel adaptive fuzzy FTC scheme is formulated. When the electromagnetic actuator fails, the developed control scheme can guarantee that all the vertical vibration states are stable. Eventually, the effectiveness of the presented control method is offered to illustrate by a random road surface.

Adaptive Fuzzy Finite-Time Fault-Tolerant Consensus Tracking Control for High-Order Multiagent Systems With Directed Graphs.

This article investigates the distributed adaptive fuzzy finite-time fault-tolerant consensus tracking control for a class of unknown nonlinear high-order multiagent systems (MASs) with actuator faults and high powers (ratio of positive odd rational numbers). The fault models include both loss of effectiveness and bias fault. Compared with existing similar results, the MASs considered here are more general and complex, which include the special case when the powers are equal to 1. Besides, the functions in this article are completely unknown and do not need to satisfy any growth conditions. In the backstepping framework, an adaptive fuzzy fault-tolerant consensus tracking controller is designed via adding one power integrator technique and directed graph theory so that the controlled systems are semiglobal practical finite-time stability (SGPFTS). Finally, numerical simulation results further verify the effectiveness of the developed control scheme.

Adaptive fuzzy fault-tolerant containment control for nonlinear multiagent systems based on modified distributed observer

This paper investigates the finite-time fault-tolerant containment control problem for stochastic nonlinear multiagent systems with intermittent actuator faults. A modified distributed observer is designed to estimate unmeasured states in systems. Compared with the existing result, the estimation precision of the modified observer is significantly enhanced in the presence of various uncertainties in the control channel. Moreover, this paper designs a compensation mechanism for intermittent faults to suppress the adverse effects caused by each fault. Then a finite-time fuzzy fault-tolerant containment control scheme is proposed to make all followers converge to the convex hull formed by leaders in a finite time. It is proved that all signals of closed-loop systems are semi-globally finite-time stable in probability based on the finite-time stochastic Lyapunov stability theory, and containment errors can converge to a small neighborhood of the origin. Finally, simulation studies are provided to illustrate the effectiveness of the proposed control scheme.

Fast Nonsingular Fixed-Time Fuzzy Fault-Tolerant Control for HFVs With Guaranteed Time-Varying Flight State Constraints

This article proposes a fuzzy adaptive fault-tolerant control strategy solving the fast fixed-time constrained tracking problem for hypersonic flight vehicles. To handle the actuator faults, a two-step design method is first proposed that only needs to estimate the upper and lower bounds of actuator parameters, under which the adverse influences of actuator faults (e.g., lock-in-place, loss of effectiveness, etc.) have been compensated via an adaptive fashion instead of conventional robust ways. In comparison with the state-of-the-art, a new fixed-time corollary that has proved a smaller upper bound of convergence time under the same condition of conventional fixed-time stability is presented. To avoid singularity issues often encountered in fixed-time designs, a piecewise but differentiable switching control laws whose continuity and differentiability are guaranteed everywhere through an appropriate design is introduced. Such a design not only preserves the continuity and differentiability of virtual and actual control laws, but also ensures the continuity of their time derivatives. Fuzzy logic systems are exploited to tackle continuous unknown dynamics and asymmetric time-varying barrier functions are utilized to confine flight states within some predefined compact sets all the time provided their initial conditions remain therein. This property is of great significance in dealing with the challenge that the operating regions of the flight state variables are asymmetric and time-varying in practice, especially when executing various flight missions. Comparative simulations have been performed to validate the effectiveness of the proposed control scheme in terms of fixed-time convergence, smoothness, and time-varying constraints satisfaction.

Fuzzy Adaptive Prescribed Performance Fault-Tolerant Control for HFVs with Fixed-Time Convergence Guarantee

A new fixed-time fuzzy adaptive fault-tolerant control methodology is proposed for the longitudinal dynamics of hypersonic flight vehicles (HFVs) in the presence of actuator faults, uncertain dynamics, and external disturbances. In contrast with the conventional fixed-time control schemes that typically contain the fractional powers of errors in their designs, this work develops a low-complexity control structure in the sense of removing the dependence on the need of abovementioned fractional power terms by means of prescribed performance control (PPC) method. Different from the most existing PPC approaches where the initial conditions of tracking errors are required to be known, the newly proposed prescribed performance function (PPF) can relax such restrictions through choosing properly small initial values of PPF. Fuzzy logic systems (FLSs) are employed to handle unknown dynamics, and minimal learning parameter (MLP) technique is incorporated into the design for the purpose of alleviating computation burden. Closed-loop stability is rigorously proved via Lyapunov stability theory, and simulation results are eventually given to validate the effectiveness of the proposed control strategy.