摘要： 目前二阶多智能体系统尚未明确给出自适应参数的确定方法，且系统的收敛速度较慢。为在实际应用中预测飞行器多智能体系统下一时刻的状态并提高收敛速度，提出一种参数自适应的一致性算法。将当前智能体间位置和速度的差值作为一致性协议的反馈参数，研究固定拓扑和切换拓扑情形下二阶多智能体系统的有限时间一致性问题，构造Lyapunov函数，同时利用LaSalle不变集原理和齐次理论，得到系统在有限时间内达到稳定的条件，实现对不同飞行器输入状态的自适应调节。仿真结果表明，该算法能够保证多智能体系统在有限时间内实现一致跟踪，且收敛速度较快。

关键词: 有限时间一致性, 二阶多智能体系统, 参数自适应算法, Lyapunov函数, 齐次理论

Abstract: The method of determining adaptive parameters is not clearly given in existing second-order multi-agent systems,and the convergence speed of systems is low.To predict the state of a multi-agent system for aircraft at the next moment in practical applications and improve the convergence speed,this paper proposes a parameter adaptive consensus algorithm.The algorithm takes the difference of location and speed between current agents as the feedback parameter of the consistency protocol.On this basis,the finite-time consistency problem of a second-order multi-agent system in the case of fixed topology and switching topology is studied.The Lyapunov function is constructed,and the LaSalle's invariant set principle and homogeneity theory are used to obtain the conditions required for the system to reach stability in finite time,so as to implement adaptive adjustment of input states of different aircrafts.Simulation results show that the proposed algorithm can ensure consistent tracking of multi-agent systems in a finite-time,and the convergence speed is fast.

Key words: finite-time consensus, second-order multi-agent systems, parameters adaptive algorithm, Lyapunov function, homogeneity theory

中图分类号: 

• TP13