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Adaptive Neural Network Fault-Tolerant Consensus Control for Multi-agent Systems with Time-Delay and Asymmetric Error Constraint
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Adaptive Neural Network Fault-Tolerant Consensus Control for Multi-agent Systems with Time-Delay and Asymmetric Error Constraint
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Adaptive Neural Network Fault-Tolerant Consensus Control for Multi-agent Systems with Time-Delay and Asymmetric Error Constraint
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Journal Article
Adaptive Neural Network Fault-Tolerant Consensus Control for Multi-agent Systems with Time-Delay and Asymmetric Error Constraint
2023
Overview
In this paper, an adaptive neural network (NN) fault-tolerant controller is designed for the leader-following consensus control problem of a nonlinear multi-agent systems (MASs) under the complex effect of actuator fault, state time-delay, asymmetric output error constraint and the lumped uncertainty. Firstly, by using an asymmetric barrier Lyapunov function (BLF), output errors are ensured to meet the asymmetric output error constraint requirements. Then, Lyapunov–Krasovskii (L–K) functional and Young’s inequality are combined to tackle state time-delay. Radial basis function neural network (RBFNN) is employed to approximate the unknown nonlinear function. Furthermore, adaptive technique is utilized to solve actuator fault. Based on the Lyapunov stability theory, the semi-global bounded stability of closed-loop system is proved. Finally, the validity of the designed control strategy is verified by compared simulation and the application of the two-stage chemical reactors.
