Fault-tolerant Consensus Control Research Articles

Simultaneous fault-tolerant consensus control and disturbance suppression for multi-agent systems with polynomial form fault under switching topology

For continuous-time linear leader-follower multi-agent systems with polynomial faults, the problem of fault-tolerant state consensus under switching topologies is studied. firstly, the average dwell time method is introduced, and observers are designed for different topologies to observe faults and disturbances. Secondly, according to the observed estimated value, the corresponding fault-tolerant control consensus protocol is proposed considering the switching situation of the communication topology. Finally, both theoretical analysis and simulation examples verify that the proposed design scheme can compensate faults and disturbance rejection.

Distributed Fault-Tolerant Consensus Control of Vehicle Platoon Systems With DoS Attacks

Distributed Fault-Tolerant Consensus Control of Vehicle Platoon Systems With DoS Attacks

Observer-based reinforcement learning for optimal fault-tolerant consensus control of nonlinear multi-agent systems via a dynamic event-triggered mechanism

In this article, an adaptive optimized consensus tracking control problem is studied for nonlinear strict-feedback dynamic multi-agent systems (MASs), considering both unmeasurable system states and time-varying bias faults. By utilizing the backstepping technique, we develop an adaptive reinforcement learning (RL) algorithm within the observer-critic-actor architecture, specially designed to compensate for the lack of state information and derive control inputs, thereby achieving approximate optimal control. Moreover, an event-triggered mechanism is introduced in the sensor-to-controller channel, which dynamically adjusts the triggering threshold online and employs event-sampled states to initiate control actions. To address discontinuities caused by state triggering, we construct virtual controllers that continuously sample state signals and reconfigure the actual controller based on previously triggered states. The outputs of the MASs are shown to accurately track the desired reference signals while ensuring the boundedness of all closed-loop signals. Additionally, the proposed controller is verified to be devoid of Zeno behavior. Finally, the effectiveness of our control methodology is demonstrated through numerical simulation.

Fault-Tolerant Optimal Consensus Control for Heterogeneous Multi-Agent Systems

This study explores fault-tolerant consensus in leader–following heterogeneous multi-agent systems, focusing on actuator failures in uncrewed aerial vehicles (UAVs) and uncrewed ground vehicles (UGVs). An optimization-based fault-tolerant consensus algorithm is proposed. The algorithm utilizes the Euler–Lagrange formula to ensure system consistency under actuator failures, with the Lyapunov stability theory proving the asymptotic stability of the consistency error. The algorithm is applied to heterogeneous multi-agent systems of UAVs and UGVs to derive optimal fault-tolerant consensus control laws for each vehicle type. Simulation experiments give evidence for the feasibility of the proposed control strategy.

Global Distributed Fault-Tolerant Consensus Control of Nonlinear Delayed Multiagent Systems With Hybrid Faults

Global Distributed Fault-Tolerant Consensus Control of Nonlinear Delayed Multiagent Systems With Hybrid Faults

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.

Failure-distribution-dependent leader-following fault-tolerant consensus for multiagent system with cyberattacks

This article concentrates on a failure-distribution-dependent leader-following fault-tolerant consensus control for multiagent systems with cyberattacks. First, considering the characteristic of failures, a failure distribution model which is more in line with the actual situation is established. To reduce the influence of zero initial conditions, an [Formula: see text] performance index suitable for leader-following multiagent systems is constructed. After this, it is difficult to obtain the augmented form of the closed-loop system due to the coupling of parameters caused by cyberattacks. Thus, based on the provided failure model and performance index, a new fault-tolerant controller is designed by using topological structure segmentation to satisfy the leader-following multiagent system fault-tolerant consensus. Finally, a numerical example is shown to prove the feasibility of this algorithm.

Distributed Fault Tolerant Consensus Control of Nonlinear Multiagent Systems via Adaptive Dynamic Programming.

This article develops a distributed fault-tolerant consensus control (DFTCC) approach for multiagent systems by using adaptive dynamic programming. By establishing a local fault observer, the potential actuator faults of each agent are estimated. Subsequently, the DFTCC problem is transformed into an optimal consensus control problem by designing a novel local value function for each agent which contains the estimated fault, the consensus errors, and the control laws of the local agent and its neighbors. In order to solve the coupled Hamilton-Jacobi-Bellman equation of each agent, a critic-only structure is established to obtain the approximate local optimal consensus control law of each agent. Moreover, by using Lyapunov's direct method, it is proven that the approximate local optimal consensus control law guarantees the uniform ultimate boundedness of the consensus error of all agents, which means that all following agents with potential actuator faults synchronize to the leader. Finally, two simulation examples are provided to validate the effectiveness of the present DFTCC scheme.

Memory-Based Event-Triggered Fault-Tolerant Consensus Control of Nonlinear Multi-Agent Systems and Its Applications

Memory-Based Event-Triggered Fault-Tolerant Consensus Control of Nonlinear Multi-Agent Systems and Its Applications

Distributed Event-Triggered Fault-Tolerant Consensus Control of Multi-Agent Systems Under DoS Attacks

Distributed Event-Triggered Fault-Tolerant Consensus Control of Multi-Agent Systems Under DoS Attacks

Adaptive Event-Triggered Fixed-Time Fault-Tolerant Consensus Control for a Class of Multiagent Systems

Adaptive Event-Triggered Fixed-Time Fault-Tolerant Consensus Control for a Class of Multiagent Systems

Self-triggered fixed-time bipartite fault-tolerant consensus for nonlinear multiagent systems with function constraints on states

This article presents a self-triggered bipartite fault-tolerant consensus control scheme in a fixed-time stability sense for multiagent systems (MASs) with function constraints on states. Neural networks are introduced to identify unknown nonlinearities, thereby relaxing constraints on unknown functions. Then, based on time-varying barrier Lyapunov functions including time and previous states, all states of the considered MASs are constrained to given ranges. In addition, to improve the utilization of system transmission resources, a self-triggered control method in which the next triggering time can be computed according to the current information of the controller is proposed. By applying the Lyapunov theory, the designed self-triggered controller can ensure that all signals containing consensus tracking errors are fixed-time bounded under a given communication topology, and the Zeno phenomenon is successfully avoided. Finally, a practical example is provided to testify the feasibility of the developed control scheme.

Adaptive fault-tolerant consensus control of multi-agent systems with event-triggered inputs

Adaptive fault-tolerant consensus control of multi-agent systems with event-triggered inputs

Fault-Tolerant Consensus Control of Positive Networked Systems

In this paper, we explore the consensus of positive networked systems with actuator faults. Firstly, the undirected and strongly connected topology is established with graph theory. The positive system theory is used to analyze the positive consensus of the closed-loop networked systems. State feedback gains are derived utilizing Algebraic Riccati Inequalities. Bounded multiplicative faults are regarded as uncertainties in the system matrix, while treating additive faults as external disturbances. Further, this transformation refocuses the analysis on the consensus problem with an L2-gain. Subsequently, the Genetic Algorithm is employed to optimize the L2 performance criteria. Finally, the effectiveness of the proposed theory is validated through simulations involving both single-input electric circuit systems and multi-input networked systems.

Adaptive Iterative Learning Fault-Tolerant Consensus Control of Multiagent Systems Under Binary-Valued Communications.

In this article, the iterative learning averaging consensus problem is studied for multiagent systems with system uncertainties, actuator faults, and binary-valued communications. Considering only binary-valued measurement information with stochastic noise can be received from its neighbors for each agent, a new two-iteration-scale framework that alternates estimation and control is designed. Under the proposed framework, each agent estimates the neighbors' states based on the empirical measurement method during a dwell iteration interval, during which each agent's states will keep constant along the iteration axis. Further, in view of the impacts of system uncertainties and actuator faults, a novel adaptive iterative learning fault-tolerant averaging consensus control scheme is designed based on its own states and the estimated neighbors' states. Finally, the resulting closed-loop system is rigorously proved to be stable, and numerical simulations are conducted to demonstrate the effectiveness of the developed control strategy.

Synchronous fault-tolerant consensus control and disturbance rejection for leader-following multi-agent systems with fault of polynomial form

This article studies the design problem of fault-tolerant and disturbance rejection control for leader-following multi-agent systems with polynomial form fault. First, a novel observer is designed to estimate polynomial form faults and external disturbances in the tracker. Second, a fault-tolerant control protocol is designed for each follower based on the obtained estimates; the designed distributed controller can effectively achieve both the goal of fault-tolerant control and the effect of disturbance rejection. Finally, a simulation result of a practical example is presented to verify the feasibility of the proposed scheme.

Robust Adaptive Event-Triggered Fault-Tolerant Consensus Control of Multiagent Systems With a Positive Minimum Interevent Time

The distributed fault-tolerant (FT) consensus control problem of linear multiagents with disturbances is considered in this article. For undirected graphs, first, by introducing adaptive control coefficients, multiagent reliable control can be carried out fully distributed, removing the assumption that global information should be known prior. Furthermore, different from existing consensus FT studies, the limitation of continuous communication among agents is removed by developing an open-loop estimation and event-triggering mechanism (ETM). Particularly, distinct from some dwell-time methods that enforce an interevent time greater than zero at the expense of asymptotic stability, by introducing timer variables, positive interevent time and asymptotic stability can be guaranteed simultaneously by the proposed ETM in the absence of disturbances. Furthermore, a minimum positive trigger interval can be maintained for each agent even in the presence of disturbances, indicating the robustness of the event-triggered strategy. It is demonstrated that the suggested event-triggered control method performs reliable disturbance suppression for all agents in a completely distributed way with intermittent communication while excluding the Zeno behavior. Moreover, we try to generalize our results to directed strong connectivity. Finally, simulation examples are carried out to illustrate the efficacy of the suggested scheme.

Adaptive Neural Network Fault-Tolerant Consensus Control for Multi-agent Systems with Time-Delay and Asymmetric Error Constraint

Adaptive Neural Network Fault-Tolerant Consensus Control for Multi-agent Systems with Time-Delay and Asymmetric Error Constraint

Adaptive fault-tolerant consensus control for nonlinear multi-agent systems, with application in micro-grids

Adaptive fault-tolerant consensus control for nonlinear multi-agent systems, with application in micro-grids

Sliding mode fault-tolerant consensus control for heterogeneous multi-agent systems based on finite-time observer and controller

This paper mainly investigates the fault-tolerant consensus problem for leader-following heterogeneous multi-agent systems with actuator faults. The model of multi-agent systems is reconstructed and the lumped faults, including external disturbances and actuator faults, are constructed. A new adaptive super-twisting sliding mode observer (ASTSMO) is constructed to estimate the undetectable lumped faults. The time-varying gain is introduced to solve the initial error problem and peak value problem. Then, based on the estimated results, an integral terminal sliding mode controller (ITSMC) is designed by integrating the fixed-time stability theory, which can effectively eliminate the nonlinear term and lumped faults. Finally, simulations are provided to illustrate the effectiveness and benefits of the proposed theoretical results.