Fault-tolerant Cooperative Control Research Articles

Symmetric Collaborative Fault-Tolerant Control of Multi-Intelligence under Long-Range Transmission in Air–Ground Integrated Wireless High-Mobility Self-Organizing Networks

With the continuous development and progress of wireless self-organizing network communication technology, how to carry out long-distance cooperative control of multiple intelligences under the framework of an air–ground integrated wireless high-mobility self-organizing network has become a hot and difficult topic that needs to be solved urgently. This paper takes the air–ground integrated wireless high-mobility self-organizing network system as the basic framework and focuses on solving the long-distance cooperative fault-tolerant control of multi-intelligent bodies and the topological stability of a wireless mobile self-organizing network. To solve the above problems, a direct neural network with a robust adaptive fault-tolerant controller is designed in this paper. By constructing a symmetric population neural network model and combining it with the Lyapunov stabilization criterion, the system feedback matrix K has the ability of autonomous adaptive learning, and symmetrically distorts, rotates, or scales the training data to instantly adjust the system’s fault-tolerant corrections and adaptive adjusting factors to resist the unknown disturbances and faults, to achieve the goals of multi-intelligent body stable control and the stable operation of a wireless high-mobility self-organizing network topology. Simulation results show that with the feedback adjustment of the multi-system under the designed controller, the multi-system as a whole has good fault-tolerant performance and autonomous learning approximation performance, and the tracking error asymptotically converges to zero. The experimental results show that the multi-flight subsystems fly stably, the air–ground integrated wireless high-mobility self-organizing network topology has good stability performance, and the maximum relative improvement of the topology stability performance is 50%.

Neural-Network-Based Adaptive Fault-Tolerant Cooperative Control of Heterogeneous Multiagent Systems With Multiple Faults and DoS Attacks.

In this article, the issue of adaptive fault-tolerant cooperative control is addressed for heterogeneous multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with actuator faults and sensor faults under denial-of-service (DoS) attacks. First, a unified control model with actuator faults and sensor faults is developed based on the dynamic models of the UAVs and UGVs. To handle the difficulty introduced by the nonlinear term, a neural-network-based switching-type observer is established to obtain the unmeasured state variables when DoS attacks are active. Then, the fault-tolerant cooperative control scheme is presented by utilizing an adaptive backstepping control algorithm under DoS attacks. According to Lyapunov stability theory and improved average dwell time method by integrating the duration and frequency characteristics of DoS attacks, the stability of the closed-loop system is proved. In addition, all vehicles can track their individual references, while the synchronized tracking errors among vehicles are uniformly ultimately bounded. Finally, simulation studies are given to demonstrate the effectiveness of the proposed method.

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.

Distributed resilient fault-tolerant cooperative automatic generation control and multi-event triggering mechanism co-design for wind energy conversion power system

In wind energy conversion power system, some sensor and actuator fall into abnormal condition which may lead to lower wind energy utilization rate and poor system performance or even system collapse. Meanwhile, with the increasing complexity of wind energy conversion power system, more device nodes compete for limited network communication resources, there are time-delays and packets dropout in data transmission, and these may reduce the efficiency of wind energy conversion. Accordingtoaboveconsideration, the multi-event triggering mechanism based distributed resilient fault-tolerant cooperative control scheme for wind energy conversion power system is put forward. A novel model of the wind energy conversion power system is established when the sensor and actuator faults simultaneously. According to Lyapunov stability theory, the sufficient condition for system exponential mean-square stable is obtained. Different from previous fault-tolerant control method, the proposed control strategy considered the wind energy conversion power system with data transmission management under simultaneous stochastic sensor and actuator faults. The simulation demonstrates that the method proposed in this paper is effective and the multi-event triggering mechanism based distributed resilient fault-tolerant controller provides stronger reliability and higher wind energy utilization efficiency.

Neuroadaptive Cooperative Fault-Tolerant Control of Heterogeneous Multiagent Systems Based on Fully Actuated System Approaches.

The leader-following cooperative problem in heterogeneous multiagent systems (HMASs) with unmodeled dynamics and actuator faults is investigated in this article. The HMASs, which include unmanned ground vehicles and unmanned aerial vehicles, are first described using a fully actuated system model (FASM). The FASM, as opposed to the first-order state-space model, preserves the physical significance of original systems and makes it feasible to apply the control rule entirely. In order to approximate unknown system dynamics, novel neuroadaptive laws with few learning parameters are then suggested. To counteract the negative effects of actuator faults, the Nussbaum function and adaptive approach are utilized. In addition, a cooperative fault-tolerant protocol is suggested, wherein consensus errors are uniformly ultimately bounded. The lack of virtual control variables in the proposed protocol reduces its complexity. The theoretical results are then validated by numerical simulations.

Overview of Cooperative Fault-Tolerant Control Driven by the Full Information Chain of Intelligent Connected Vehicle Platoons Under the Zero-Trust Framework: Opportunities and Challenges

Overview of Cooperative Fault-Tolerant Control Driven by the Full Information Chain of Intelligent Connected Vehicle Platoons Under the Zero-Trust Framework: Opportunities and Challenges

Cooperative Fault-Tolerant Control for a Class of Nonlinear MASs by Resilient Learning Approach.

In this article, a learning-based resilient fault-tolerant control method is proposed for a class of uncertain nonlinear multiagent systems (MASs) to enhance the security and reliability against denial-of-service (DoS) attacks and actuator faults. With the framework of cooperative output regulation, the developed algorithm consists of designing a distributed resilient observer and a decentralized fault-tolerant controller. Specifically, by using the data-driven method, an online resilient learning algorithm is first presented to learn the unknown exosystem matrix in the presence of DoS attacks. Then, a distributed resilient observer is proposed working against DoS attacks. In addition, based on the developed observer, a decentralized adaptive fault-tolerant controller is designed to compensate for actuator faults. Moreover, the convergence of error systems is shown by using the Lyapunov stability theory. The effectiveness of our result is examined by a simulation example.

Virtual Coupling-Based H∞ Active Fault-Tolerant Cooperative Control for Multiple High-Speed Trains With Unknown Parameters and Actuator Faults

This paper investigates the cooperative control problem of multiple high-speed trains subject to unknown parameters and actuator faults. The cooperative operation of multiple high-speed trains is modeled as a coupled control system. On the basis of the virtual coupling technique, the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> active fault-tolerant cooperative control scheme is established to guarantee the desired tracking performances and cooperative performances. The adaptive control technique is adopted to estimate the unknown Davis’ coefficients and the fault parameters and linear matrix inequalities are utilized to derive the control gain of the cooperative control protocols for the trains. Rigorous analysis is provided to corroborate the closed-loop stability of the cooperative train control system and numerical simulation is conducted to verify the effectiveness and feasibility of the proposed results.

Distributed cooperative fault tolerant optimal active power control in AC microgrid

In this paper, a new distributed and cooperative fault tolerant control is proposed for the double-function optimal active power control (APC) of distributed generators (DG) in an islanded AC microgrid. Double-function optimal APC consists of the economic dispatch which calculates the optimal active power set-points and coordinates control modules to receive and track the set-points. In the proposed control method, if there is a faulty DG whose capability to satisfy its optimum active power set-point is restricted due to a totally or partially DG failure, the task of reaching the global control goal is re-distributed among the fault-free DGs through designing dynamic feedback set-points. In addition, no central coordinator is considered for the MG, and the new set-points are calculated locally by the fault-free DGs through message exchange over the communication network. Redistribution is performed without requiring any coordination unit and only with the cooperation of DGs on redistributed set-points through local exchange information. The capability of the proposed method is evaluated by considering a microgrid with multiple DGs and analyzing its operational performance under a variety of fault scenarios, as well as providing a qualitative and quantitative comparison with existing literature to demonstrate its efficacy.

Fault Detection and Fault-Tolerant Cooperative Control of Multi-UAVs under Actuator Faults, Sensor Faults, and Wind Disturbances

Fault detection (FD) and fault-tolerant cooperative control (FTCC) strategies are proposed in this paper for multiple fixed-wing unmanned aerial vehicles (UAVs) under actuator faults, sensor faults, and wind disturbances. Firstly, the faulty model is introduced while the effectiveness loss, deviation of thrust throttle setting, and pitot sensor faults are considered. Secondly, the faulty UAV model with wind disturbances is linearized and the system is then converted into two subsystems by using state and output transformations. Further, cooperative unknown input observers (UIOs) are developed to estimate the faults, disturbances, and states. By combining with the observers’ estimations, adaptive thresholds are designed to detect actuator and sensor faults in the system. Then, considering state constraints, a backstepping-based FTCC scheme is proposed for multiple UAVs (multi-UAVs) suffering from actuator faults, sensor faults, and wind disturbances. It is shown by Lyapunov analysis that the tracking errors are fixed-time convergent. Finally, the effectiveness of the FD and FTCC scheme is verified by numerical simulation.

Distributed Active Fault-Tolerant Cooperative Control for Multiagent Systems With Communication Delays and External Disturbances.

This article investigates the distributed active fault-tolerant cooperative control problem for leader-follower multiagent systems (MASs) in the presence of multiple faults, communication delays, and external disturbances. A new distributed consensus protocol is put forward to ensure the state consensus of MASs, which can be served as a nominal controller in fault-free cases with communication delays and external disturbances. A novel distributed time-delay intermediate observer, which can estimate system states and multiple faults simultaneously, is derived based on the time-delay closed-loop system equation. By integrating a fault compensation mechanism into the nominal controller, a distributed active fault-tolerant consensus controller is constructed for the follower agents to eliminate the adverse effects of multiple faults. Simulation examples are provided to demonstrate the effectiveness of the proposed method.

Resilient Event-Triggered Adaptive Cooperative Fault-Tolerant Tracking Control for Multiagent Systems Under Hybrid Actuator Faults and Communication Constraints

This paper investigates the cooperative fault-tolerant tracking problem for multiagent systems with directed topology that experience communication link faults and actuator faults under malicious attacks. Based on a resilient event-triggered mechanism, a novel distributed high-order sliding-mode observer and a robust adaptive cooperative fault-tolerant control method are proposed, which can achieve the desired formation shape tracking under communication limitations and hybrid actuator faults caused by malicious attacks. First, the designed distributed event-triggered observer can estimate the unknown leader. Second, the proposed event-triggered mechanism can be used to reduce the impact of malicious attacks on the information and physical layers of the multiagent system. Additionally, the utilization rate of network communication is further improved so that it can save communication resources by reducing the number of event triggers. Then, based on the information of the leader, the designed robust adaptive cooperative fault-tolerant controller can compensate for the influence of the hybrid actuator faults on the system under malicious attacks. Finally, the effectiveness of the method is verified by two sets of example simulations.

Distributed adaptive event‐triggered fault‐tolerant cooperative control of multiple UAVs and UGVs under DoS attacks

AbstractHere, the issue of distributed adaptive event‐triggered fault‐tolerant cooperative control (FTCC) is studied for multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) in the presence of actuator faults under denial‐of‐service attacks. To save the limited communication network resources, the distributed adaptive event‐triggered FTCC scheme is investigated for the multiple UAVs and UGVs which does not require continuous information relating to its neighbours. It is proven that the tracking errors are uniformly ultimately bounded by utilizing the Lyapunov function approach. Furthermore, the Zeno behaviour is excluded with the proposed scheme. Finally, simulation studies are provided to demonstrate the efficiency of the proposed scheme.

Distributed Cooperative Fault-Tolerant Control of High-Speed Trains With Input Saturation and Actuator Faults

In this work, a novel distributed fault-tolerant control strategy is proposed for cooperative operation of high-speed trains (HSTs) subject to unmodeled dynamics, time-varying external disturbances, input saturation and actuator partial failures. The cooperative control of HSTs is first transformed to the consensus problem of a multi-agent system. Then, the distributed control laws that are equipped with a command filter and an adaptive neural network are developed to achieve the consensus task among the HSTs with predefined displacement and speed profiles. Further, an auxiliary dynamical system is introduced to compensate for the influence of input saturation. Moreover, an adaptive failure compensation strategy is designed to deal with the unknown and time-varying actuator faults. The convergence of the proposed controller is analyzed rigorously by applying the Lyapunov theorem, and the effectiveness is demonstrated by numerical simulations.

Fractional Order Nonsingular Terminal Sliding Mode Cooperative Fault-Tolerant Control for High-Speed Trains With Actuator Faults Based on Grey Wolf Optimization

Fractional Order Nonsingular Terminal Sliding Mode Cooperative Fault-Tolerant Control for High-Speed Trains With Actuator Faults Based on Grey Wolf Optimization

Decentralized Adaptive Fault-Tolerant Cooperative Control for Multiple UAVs with Input Saturation and State Constraints

This paper proposes a fault-tolerant cooperative control (FTCC) scheme for multiple UAVs in a distributed communication network against input saturation, full-state constraints, actuator faults, and unknown dynamics. Firstly, by considering physical limitations, an auxiliary control signal is designed to simplify the analysis process. Secondly, to avoid the difficulty in the back-stepping design caused by full-state constraints, virtual control signals are constructed to transform constrained variables, while the dynamic surface control is adopted to avoid the phenomenon of “differential explosion.” Thirdly, a disturbance observer (DO) is designed to estimate the unknown uncertainty caused by parameter uncertainty and actuator fault. Moreover, a recurrent wavelet fuzzy neural network (RWFNN) is used to compensate for the estimation errors of DO. Finally, it is proved that all states are uniformly ultimately bounded (UUB) by Lyapunov and invariant set theory. The effectiveness of the proposed scheme is further demonstrated by the simulation results.

Cooperative Fault-Tolerant Control for a Mobile Dual Flexible Manipulator With Output Constraints

This article discusses cooperative control of a mobile dual flexible manipulator system with asymmetric time-varying output constraints and actuator failures. The shift function and a barrier Lyapunov function (BLF) are used to guarantee output constraints when the initial states of the system violate the prescribed constraints. Moreover, an adaptive fault-tolerant control scheme is developed to deal with actuator failures, while suppressing system’s vibration and achieving cooperative operation. Finally, theoretic analysis proves the uniform bounded stability of the system and numerical simulation verifies the effectiveness of the proposed control method. Note to Practitioners—The purpose of this article is to develop a cooperative dual flexible manipulator system with performance limitations and actuator failures. The system can realize the task of stably grasping and moving a rigid object. The existing research on the grasping task of flexible manipulators only focuses on coordinated operation, which limits the application of the dual flexible manipulator system in practical engineering. To further study the problem, this article considers the output constraints and actuator failures of the dual flexible manipulator system in the actual process and proposes a cooperative fault-tolerant control framework. The control framework uses shift function and BLF to deal with output constraints and adopts adaptive technology to deal with actuator failures. In addition, the cooperative operation task of grasping object with dual flexible manipulators is realized. Simulation shows that this control strategy is feasible.

Neural network-based smooth fixed-time cooperative control of high-Order multi-agent systems with time-varying failures

This article tries to achieve smooth fixed-time cooperative control for high-order multi-agent systems in the presence of nonlinear uncertainties, time-varying failures and single-way communication. Due to the lemma of fixed-time stabilization involving fractional and high-power terms, it is nontrivial to design C1 smooth controllers for such systems. To eliminate linear growth conditions of uncertainties, neural networks are introduced; To ensure all fixed-time controllers are C1 continuous, a novel smooth fixed-time cooperative control framework is provided by designing C1 smooth switching and implementing dynamic surface control such that singularity and chattering problem are eliminated completely; To achieve smooth fixed-time fault-tolerant control, based on bound estimation method, the fixed-time compensation of time-varying failures is made by designing two continuous adaptive laws. Then, a novel smooth fixed-time fault-tolerant cooperative control scheme is proposed to guarantee that all control signals are continuous, smooth and bounded. Meanwhile, all internal errors will converge to arbitrarily small zones of zero within fixed time. To confirm the effectiveness of the proposed smooth fixed-time fault-tolerant cooperative control schemes, simulations based on a numerical example and a practical example are made.

Fixed-time attitude cooperative fault-tolerant control with prescribed performance for heterogeneous multiple satellite

This paper mainly investigates the fixed-time cooperative fault-tolerant control problem for heterogeneous satellite attitude control systems with external disturbances, actuator faults, and unknown inertia uncertainties. Firstly, the asymmetric prescribed performance mechanism is utilized to impose desired performance functions on satellite attitude tracking errors. Then, the fixed-time neuroadaptive technique is adopted to approximate unknown system uncertainties, and a novel fixed-time fault-tolerant controller is thus proposed to ensure that the transformed tracking errors converge to a small neighborhood of origin within a fixed time. Moreover, the Lyapunov theory is employed to validate that the closed-loop system is fixed-time stability under the control scheme. Finally, simulations results are carried out to verify the effectiveness of proposed strategy.

Fault-Tolerant Cooperative Control for Multiple Vehicle Systems Based on Topology Reconfiguration.

In this article, the fault-tolerant synchronization and time-varying tracking control problem is investigated for nonlinear multivehicle systems (MVSs) in the presence of partial loss-of-control-effectiveness (LoCE) faults. Based on the graph theory, a two-level fault-tolerant cooperative control framework is proposed, namely, the low-level distributed nominal control scheme and the high-level topology reconfiguration protocols. The low-level scheme is developed to guarantee system performances in the fault-free scenario. With the low-level scheme, the high-level topology reconfiguration protocols, each of which corresponds to one partial LoCE fault scenario, are then proposed to mitigate the fault impact by adjusting the underlying topology. Accordingly, without modifying the structure or the design parameter of the low-level control scheme, the proposed framework can guarantee the synchronization and tracking errors of the MVS asymptotically convergent to zero in both fault-free and fault scenarios. Finally, the effectiveness of the proposed control method is verified via a simulation study of three degree-of-freedom helicopters.