执行器饱和多智能体系统的自适应学习一致性算法  

Adaptive learning consensus algorithm for multi-agent systems with actuator saturations

作　　者：杨娜娜[1] 孟新友[1] 王璇[1] Yang Nana;Meng Xinyou;Wang Xuan(School of Science,Lanzhou University of Technology,Lanzhou 730050,China)

机构地区：[1]兰州理工大学理学院,兰州730050

出　　处：《计算机应用研究》2021年第9期2737-2740,共4页Application Research of Computers

基　　金：甘肃省教育厅创新基金资助项目(2021A-025);国家自然科学基金地区资助项目(11661050,12064024);兰州理工大学红流一级学科建设项目。

摘　　要：针对一类受到执行器饱和高阶多智能体系统在有限时间区间[0,T]上的精确一致性问题,利用自适应迭代学习控制的方法,设计了具有全饱和差分型自适应更新律的时变增益。通过构造适当的复合能量函数,严格证明了一致性误差向量随着迭代次数趋于无穷而一致趋于零,得到了不依赖于网络通信拓扑矩阵特征值的自适应学习一致性算法。最后,给出一个仿真例子,仿真结果说明了所提算法的有效性。To settle the exact consensus problem of a class of multi-agent systems subjected to actuator saturations on a finite time interval[0,T],this paper utilized the adaptive iterative learning control scheme to design the time-varying gains with fully saturated difference adaptive updating laws.By constructing a proper composite energy function,it was proved strictly that the vectors of consensus error tended to zero as the iteration number approaches to infinity,and obtained the adaptive learning consensus algorithm without dependence on eigenvalues of the communication topology matrix.Finally,the result of a given simulation example illustrates the effectiveness of the proposed algorithm.

关 键 词：多智能体系统 执行器饱和 迭代学习控制 自适应控制 一致性 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]