Fault-tolerant Control Problem Research Articles

Adaptive sliding mode and RBF neural network based fault tolerant attitude control for spacecraft with unknown uncertainties and disturbances

Taking the external disturbance, model uncertainty, actuator failure, and actuator saturation into consideration, this paper investigates the nonlinear fault-tolerant attitude control problem for the spacecraft. First, to deal with the disturbance and uncertainty with unknown boundaries, an adaptive sliding mode control method is proposed to stabilize the state variables of the spacecraft attitude control system. Then the actuator failure and saturation are further considered, and the second spacecraft fault-tolerant attitude controller is derived based on adaptive sliding mode control and radial basis function (RBF) neural networks. The adaptive control gains reduction technique is applied in the design process, which can weaken the chattering phenomenon of the controller to some extent, and the stability of the attitude control system is analyzed through Lyapunov theory. In the proposed controller, model information and external disturbance are not required and only the system states are needed. Furthermore, the boundaries of the model uncertainty, external disturbance, actuator fault and saturation are assumed to be existing but unknown by the proposed controllers. These features make the proposed attitude controllers need few modeling information of the spacecraft, or maintain strong robustness even if the model or external environment occurs significant changes. Finally, numerical simulations demonstrate the great performance of the proposed fault-tolerant attitude control method.

Prescribed-time fault-tolerant tracking control for Markov jump nonlinear systems based on saturation dynamics filters

This paper investigates the problem of prescribed-time fault-tolerant tracking control for a class of Markov jump nonlinear systems affected by actuator faults and input saturation. First, a new time-varying constraint function and an error transformation are invoked to transform the original prescribed-time tracking control problem into a tracking control problem with deferred constraint for tracking error. Furthermore, the parameter correction terms are designed, on which a novel Markov jump saturation dynamic filter is constructed to handle the unfavorable effect of input saturation. Meanwhile, the projection operator technique and the norm estimation methodology are integrated to devise adaptive laws to estimate the unknown actuator faults evolving in accordance with the Markov chain. A new prescribed-time fault-tolerant tracking control scheme is put forward that realizes the deferred constraint on the tracking error, which in turn ensures that the tracking error of the system converges to a prescribed accuracy within a prescribed-time. Finally, two simulation examples, one of which implements a prescribed-time fault-tolerant tracking control for rotary steerable drilling tool system, are presented to illustrate the effectiveness and practicality of the developed scheme.

Research on fault-tolerant control methods for Bi-rotor vehicles under actuator failure

A PID-self-impedance fault-tolerant controller based on the inner and outer loop structure is developed for a new form of bi-rotor vehicle, taking into account the fault-tolerant control problem when the actuator fails. First, the dynamics model and actuator fault model of the bi-rotor vehicle are established, the PID active fault-tolerant controller with control parameter switching is selected for the outer loop, and the self-immune controller is selected for the inner loop. Second, when a fault occurs, the outer loop PID controller’s settings are switched to the controller parameters of the relevant fault state based on the extent of the fault, and the parameters are matched with the robust controller of the inner loop to achieve fault-tolerant control. Finally, simulation experiments show that the designed fault-tolerant controller can still achieve stable tracking of position and attitude in the presence of actuator faults. This indicates that the flight control system is robust to fault-induced disturbances and effectively improves the vehicle’s fault-tolerant performance.

Nonlinear disturbance observer-based geometric attitude fault-tolerant control of quadrotors

This paper is concerned with nonlinear disturbance observer (DO)-based geometric attitude fault-tolerant control (FTC) problem of quadrotor unmanned aerial vehicles (UAVs) subject to system uncertainties, exogenous disturbances, and actuator faults. A disturbance observer-based control (DOBC) framework is devised to tackle the difficulties caused by system uncertainties and external disturbances. The FTC is proposed to cope with the occurrence of actuator faults which can be modelled as a constant loss of effectiveness. The proposed design scheme can provide an effective way to analyse the stability of the closed-loop system, which can ensure the asymptotical convergence of the error. The other method considers actuator failures as part of the lumped disturbance, and the attitude tracking problem of quadrotors concerning the lumped disturbance is solved by the DO-based control method, which can ensure the exponential convergence of the error. The numerical simulations are performed to illustrate the effectiveness of the design techniques.

Robust Cooperative Fault-Tolerant Control for Uncertain Multi-Agent Systems Subject to Actuator Faults.

This article investigates the robust cooperative fault-tolerant control problem of multi-agent systems subject to mismatched uncertainties and actuator faults. During the design process of the intermediate variable estimator, there is no need to satisfy fault estimation matching conditions, and this overcomes a crucial constraint of traditional observers and estimators. The feedback term of the designed estimator contains the centralized estimation errors and the distributed estimation errors of the agent, and this further improves the design freedom of the proposed estimator. A novel fault-tolerant control protocol is designed based on the fault estimation information. In this work, the bounds of the fault and its derivatives are unknown, and the considered method is applicable to both directed and undirected multi-agent systems. Furthermore, the parameters of the estimator are determined through the resolution of a linear matrix inequality (LMI), which is decoupled by employing coordinate transformation and Schur decomposition. Lastly, a numerical simulation result is used to demonstrate the effectiveness of the proposed method.

Multi-group formation tracking fault-tolerant control for matched nonlinear multi-agent systems with switching topologies and unknown control inputs

The multi-group formation fault-tolerant control problem for high-order nonlinear multi-agent systems with parameter uncertainties, unknown external disturbances, switching topologies, and non-cooperative targets are investigated in this paper. A fully distributed formation tracking control protocol is proposed based on the total interaction information between subgroups being zero and the neighboring relative information of multi-agent in the subgroups. In addition, an algorithm is proposed to design the parameters of time-varying formation tracking control protocol. At the same time, it does not require knowing the bounds of actuator faults, parameter uncertainties, control inputs of the leaders, and unknown disturbances. Then, it is proved that the designed control protocols can make the high-order nonlinear multi-agent systems accomplish the desired time-varying multi-group formation, and the errors are uniformly asymptotically bounded stable. Finally, the effectiveness of the designed control protocol is demonstrated by simulation examples of three subgroups.

Reduced-order fault estimation observer based fault-tolerant control for switched systems

This paper studies the fault-tolerant control (FTC) problem for switched systems with actuator fault. The reduced-order observers based method is proposed to reconstruct the system state and fault, simultaneously, where the fault can be large and fast time-varying. If the disturbance is ignored, the exponentially stable estimation result can be achieved. Furthermore, the FTC strategy is considered to stabilize the systems. Under any switched law, the root-mean-square (RMS) gain is considered to realize the robustness of the discussed technique to the disturbance. Compared with the traditional H∞ performance, it not only relaxes the limitation of disturbance being with bounded energy, but also removes the requirement of zero initial condition. In the fault estimation process, the zero initial condition requires the state and fault initial values should be known, which is not needed in this paper. At last, the effectiveness of the considered technique is verified by two examples.

Integrated fault estimation and control for multi-agent systems with external disturbance using delayed relative information

This paper is dedicated to the problem of actuator fault estimation and fault-tolerant control for general linear leader–follower multi-agent systems subject to external disturbance and communication delay. First, the intermediate variable observer is constructed to estimate faults using relative information with symmetric time delays. A contradiction between the convergence speed of estimation error and the time-delay margin is revealed, where quick convergence implies small time-delay margin. As such, the augmented system observer is employed to improve the convergence speed. In the next, integrated scheme is adopted to handle the bi-directional interaction between fault estimation and fault-tolerant control arising from external disturbance and time-varying faults. In addition, we also consider the asymmetric delay case with only transmission delay. The delay-independent stability condition is derived with the use of augmented system observer by virtue of Lyapunov–Krasovskii function and [Formula: see text] robust theories. Finally, the simulation results are presented to verify the effectiveness of proposed method.

Fault-tolerant formation consensus control for time-varying multi-agent systems with stochastic communication protocol

Article Fault-tolerant formation consensus control for time-varying multi-agent systems with stochastic communication protocol Chunyu Li, Yifan Liu, Ming Gao, and Li Sheng * 1 College of Control Science and Engineering, China University of Petroleum (East China), Qingdao 266580, China * Correspondence: E-mail: shengli@upc.edu.cn Received: 4 September 2023 Accepted: 8 November 2023 Published: 26 March 2024 Abstract: This paper is concerned with the problem of fault-tolerant formation consensus control for linear time-varying (LTV) multi-agent systems (MASs) with stochastic communication protocol (SCP). The SCP is introduced to schedule the signal transmission, and only one neighbouring agent is allowed to transmit data at one instant. The purpose of this work is to design a fault-tolerant controller for each agent, so that, for all probabilistic scheduling behaviors, MASs can achieve the formation consensus performance. The state and fault are augmented into a new vector, meanwhile, each agent system is written as a singular one and a state observer is designed. By utilizing the estimated information of states and faults, the designed time-varying compensation term can reduce the impacts of unknown external disturbances and faults. Then, a sufficient condition is obtained to guarantee the performance constraint over the finite horizon for closed-loop systems. The parameters of observers and controllers are derived by solving coupled backward recursive Riccati difference equations. Finally, a numerical example is given to validate the effectiveness of the proposed fault-tolerant control scheme.

Funnel-Based Adaptive Neural Fault-Tolerant Control for Nonlinear Systems with Dead-Zone and Actuator Faults: Application to Rigid Robot Manipulator and Inverted Pendulum Systems

This study addresses an adaptive neural funnel fault-tolerant control problem for a class of strict-feedback nonlinear systems with actuator faults and input dead zone. To guarantee the boundedness of the tracking error, a modified transformation for funnel error is devised and incorporated into the control design process. To manage unknown nonlinear functions, radial basis function neural networks (RBFNN) are employed in designing an adaptive neural funnel fault-tolerant controller through the backstepping technique. The proposed controller guarantees the output tracking error stays within a predefined funnel, and all signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB). Finally, simulations of a rigid robot manipulator system and an inverted pendulum system are conducted to validate the practicality and effectiveness of the proposed control method.

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.

A Novel Failure-Distribution-Dependent Non-Fragile $H_\infty$ Fault-Tolerant Load Frequency Control for Faulty Multi-Area Power Systems

This paper studies the non-fragile <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_\infty$</tex-math></inline-formula> fault-tolerant load frequency control problem for multi-area power systems with actuator failures. At first, considering the distribution characteristics of partial failures, a stochastic distribution model is established for actuator partial failures. Next, for the perturbations of controller gains, not only the additive uncertainties but also the multiplicative uncertainties are incorporated into the fault-tolerant controller design. The coupling items which hardly directly solved have turned into a W-problem in fault-tolerant load frequency control. Furthermore, a novel failure-distribution-dependent non-fragile <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_\infty$</tex-math></inline-formula> fault-tolerant load frequency control algorithm is given by using linear matrix inequalities technology and Lyapunov-Krasovskii functional method. Finally, a numerical example with a three-area power system are given to show the effectiveness of the proposed methods.

Reinforcement Learning-Based Fractional-Order Adaptive Fault-Tolerant Formation Control of Networked Fixed-Wing UAVs With Prescribed Performance.

This article investigates the fault-tolerant formation control (FTFC) problem for networked fixed-wing unmanned aerial vehicles (UAVs) against faults. To constrain the distributed tracking errors of follower UAVs with respect to neighboring UAVs in the presence of faults, finite-time prescribed performance functions (PPFs) are developed to transform the distributed tracking errors into a new set of errors by incorporating user-specified transient and steady-state requirements. Then, the critic neural networks (NNs) are developed to learn the long-term performance indices, which are used to evaluate the distributed tracking performance. Based on the generated critic NNs, actor NNs are designed to learn the unknown nonlinear terms. Moreover, to compensate for the reinforcement learning errors of actor-critic NNs, nonlinear disturbance observers (DOs) with skillfully constructed auxiliary learning errors are developed to facilitate the FTFC design. Furthermore, by using the Lyapunov stability analysis, it is shown that all follower UAVs can track the leader UAV with predesigned offsets, and the distributed tracking errors are finite-time convergent. Finally, comparative simulation results are presented to show the effectiveness of the proposed control scheme.

Fixed-Time Fault-Tolerant Consensus Control for High-Order Nonlinear Multiagent Systems Under Directed Topology

This paper addresses the fixed-time fault-tolerant consensus control problem for high-order nonstrict-feedback nonlinear multi-agent systems under directed topology. A distributed high-order fixed-time observer is proposed to obtain the accurate estimations of the full states of the leader. Different from the fixed-time observer design methods, a much more concise estimate for the upper bound of the convergence time is provided. Based on the fixed-time observer and adding a power technique, a fixed-time tracking protocol is designed for a group of followers subject to unknown nonidentical dynamics and unpredictable actuation faults. It is shown that there is no need to know the information of the nonstrict-feedback nonlinear dynamics, the control gains, and the actuation faults in the control design and implementation completely, which is deemed favorable in practice. Simulation results are provided to validate the effectiveness of the developed control scheme.

Evolutionary Reinforcement Learning: Hybrid Approach for Safety-Informed Fault-Tolerant Flight Control

Recent research in artificial intelligence potentially provides solutions to the challenging problem of fault-tolerant and robust flight control. This paper proposes a novel Safety-Informed Evolutionary Reinforcement Learning algorithm (SERL), which combines Deep Reinforcement Learning (DRL) and neuroevolution to optimize a population of nonlinear control policies. Using SERL, the work has trained agents to provide attitude tracking on a high-fidelity nonlinear fixed-wing aircraft model. Compared to a state-of-the-art DRL solution, SERL achieves better tracking performance in nine out of ten cases, remaining robust against faults and changes in flight conditions, while providing smoother action signals.

Finite-Time Fuzzy Fault-Tolerant Control for Nonlinear Flexible Spacecraft System with Stochastic Actuator Faults

In the quest for unparalleled reliability and robustness within control systems, significant attention has been directed toward mitigating actuator faults in diverse applications, from space vehicles to sophisticated industrial systems. Despite these advances, the prevalent assumption of homogeneous actuator faults remains a stark simplification, failing to encapsulate the stochastic and unpredictable nature of real-world operational environments. The problem of finite-time fault-tolerant control for nonlinear flexible spacecraft systems with actuator faults is addressed in this paper, utilizing the T-S fuzzy framework. In a departure from conventional approaches, actuator failures are modeled as random signals following a nonhomogeneous Markov process, thus comprehensively addressing the issue of timeliness, which has previously been overlooked in the literature. To effectively manage the intricacies introduced by these factors, the nonhomogeneous Markov process is represented as a polytope set. The proposed solution involves the development of a nonhomogeneous matrix transformation, accompanied by the introduction of adaptable parameters. This innovative controller design methodology yields a stability criterion that ensures H∞ performance in a mean-square sense. To empirically substantiate the effectiveness and advantages of the proposed approaches, a numerical example featuring a nonlinear spacecraft system is presented.

Fixed-Time Fault Estimation and Prescribed Performance Fault-Tolerant Control for Interconnected Systems.

This article investigates the problem of fixed-time fault estimation and fault-tolerant control (FTC) for interconnected systems subject to both multiplicative and additive actuator faults. On the basis of the bilimit homogeneous theory, the proposed fault estimation observer can acquire the exact system state and fault information in a specified time, and such a time is determined by a constant upper bound, independent of the initial observation errors. Next, the prescribed performance function (PPF) is employed to impose the anticipant performance criterion on the trajectory tracking errors, for the purpose of preserving both desirable transient and steady-state responses. Afterward, we incorporate the recursive fast terminal sliding-mode technique into the active FTC (AFTC) design procedure to eliminate the influence of faults. In such a way, the fixed-time convergence property of tracking errors can be guaranteed without any restriction on the initial conditions. Finally, comparative simulation results are provided to illustrate the feasibility and superiority of the proposed strategy.

Prescribed-time fault-tolerant control for the formation of quadrotors based on fully-actuated system approaches

This paper investigates the problem of prescribed-time fault-tolerant control for the formation of quadrotors by utilising the fully-actuated system approach. Since not all quadrotors can directly access the virtual leader's state, a distributed prescribed-time observer is designed to estimate the state of a virtual leader. Leveraging this observer, a horizontal position controller that combines the fully-actuated system approach with the prescribed-time method, as well as altitude and attitude fault-tolerant controller, are proposed. In the design of control law, two distinct sets of controllers are designed: asymptotically stable controller and prescribed-time controller, each tailored to specific control objectives. The proposed distributed prescribed-time observer can ensure that the estimation error of the leader's state reaches zero within any specified time interval. Finally, the numerical simulation is conducted to demonstrate the effectiveness of the proposed fault-tolerant formation control algorithm.

Data-driven Second-order Sliding Mode Fault-Tolerant Control for a Class of Discrete-time Nonlinear Systems

The current paper presents a data-driven discrete-time integral second-order sliding mode fault-tolerant control (DISSM-FTC) strategy for a category of discrete-time nonlinear systems. The characteristic of the presented control strategy can be easily implemented because it only employs the system's input and output data model through a partial form dynamic linearization (PFDL) approach. At the same time, the fault diagnosis mechanism employs a time-varying threshold with prescribed performance to decide whether a fault occurs or not. Then, the DISSM-FTC method is presented, and a theoretical analysis ensures the stability of the presented strategy. Finally, the efficiency of the presented approach is confirmed through numerical simulations. In contrast to the previous works, the merits of the DISSM-FTC strategy are: 1) the fault-tolerant control problem is solved for the PFDL data model; 2) a novel fault diagnosis mechanism with prescribed performance is proposed; and 3) a data-driven DISSM-FTC method is first proposed.

Observer‐based fault tolerant control for a class of nonlinear multi‐agent systems with sensor faults

AbstractThis article focuses on the robust fault tolerant control (FTC) problem for a class of Lipschitz nonlinear multi‐agent systems(MASs) subject to sensor faults. Firstly, sensor faults are transformed into actuator faults via introducing a new intermediate auxiliary state variable, and a distributed adaptive fault estimation observer is designed to estimate the state information and the concerned faults by using the relative output estimation error. Then, the sufficient existence conditions for the observer to satisfy the robust performance index are given. Thirdly, based on the results of observer design, a new design method of dynamic output feedback controller is proposed to implement consensus of MASs and ensure the desired disturbance rejection performance. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.