Prescribed Performance Practical Fixed-Time Consensus Control for Multiagent Systems With Input Saturation
针对存在输入饱和与外部干扰的非线性不确定多智能体系统，提出一种自适应动态面设计方案，结合模糊逻辑系统与事件触发机制，实现预设性能下的固定时间一致性控制。
This study focuses on the prescribed performance practical fixed-time control problem for nonlinear uncertain multiagent systems with input saturation and external disturbances. Unlike existing practical fixed-time consensus approaches, we propose an adaptive dynamic surface design scheme to mitigate computational complexity in the backstepping procedure. In addition, fuzzy logic systems are adopted to approximate uncertainties. To reduce the frequency of controller updates, an event-triggering mechanism is introduced. Using the backstepping technique and Lyapunov stability theory, we design a real adaptive distributed fuzzy controller that can guarantee consensus errors remain within prescribed performance in a fixed time. Ultimately, emulate results express the effectiveness of the presented strategy.