Adaptive Consensus of Non-Strict Feedback Switched Multi-Agent Systems With Input Saturations  

作　　者：Zhanjie Li Jun Zhao 

机构地区：[1]Institute of Advanced Technology,Nanjing University of Posts and Telecommunications,Nanjing 210023 [2]College of Information Science and Engineering,Northeastern University,Shenyang 110819,China [3]IEEE

出　　处：《IEEE/CAA Journal of Automatica Sinica》2021年第11期1752-1761,共10页自动化学报（英文版）

基　　金：supported in part by the National Key Research and Development Program(2018YFA0702202);in part by the Leadingedge Technology Program of Jiangsu National Science Foundation(BK20202011);in part by the Research Grants of the Nanjing University of Posts and Telecommunications(NY220158,NY220177)。

摘　　要：This paper considers the leader-following consensus for a class of nonlinear switched multi-agent systems(MASs)with non-strict feedback forms and input saturations under unknown switching mechanisms.First,in virtue of Gaussian error functions,the saturation nonlinearities are represented by asymmetric saturation models.Second,neural networks are utilized to approximate some unknown packaged functions,and the structural property of Gaussian basis functions is introduced to handle the non-strict feedback terms.Third,by using the backstepping process,a common Lyapunov function is constructed for all the subsystems of the followers.At last,we propose an adaptive consensus protocol,under which the tracking error under arbitrary switching converges to a small neighborhood of the origin.The effectiveness of the proposed protocol is illustrated by a simulation example.

关 键 词：Adaptive consensus input saturation non-strict feedback switched multi-agent systems(MASs) 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]