二部图
控制理论(社会学)
非线性系统
有界函数
共识
自适应控制
计算机科学
多智能体系统
控制器(灌溉)
数学
数学优化
图形
理论计算机科学
控制(管理)
人工智能
生物
物理
数学分析
量子力学
农学
作者
Zihao Shang,Yuqiang Jiang,Ben Niu,Xudong Zhao,Ding Wang,Bin Li
标识
DOI:10.1109/tase.2023.3323469
摘要
In this paper, an adaptive finite-time bipartite consensus tracking control strategy is presented for a class of heterogeneous nonlinear nonstrict-feedback multi-agent systems (MASs) with output constraints. Firstly, to deal with the time-varying output constraints problem, an improved tan-type nonlinear mapping (NM) function is presented for the first time. And based on the improved NM function, a novel tracking error is constructed to design controller for each agent, which guarantees the bipartite consensus tracking is achieved while constraints requirement is not violated. Then, a state observer is designed to estimate the unmeasurable states of each agent. Moreover, in the case of unbalanced directed topological graph, a partition algorithm (PA) is employed to implement bipartite consensus tracking control. The developed distributed adaptive finite-time control strategy ensures that all the signals in the closed-loop system are bounded and the bipartite consensus tracking control is achieved in finite time. Finally, the validity of the designed control strategy is demonstrated by a simulation experiment. Note to Practitioners —At present, nonlinear MASs are widely used in practice, such as robots formation control, vehicular platoon systems control, etc. This paper investigated the adaptive finite-time bipartite consensus tracking control problem for a class of heterogeneous nonlinear nonstrict-feedback MASs with output constraints. In the scenarios of practical application, these two situations are common: 1) The communication topology graph of nonlinear MASs is unbalanced. 2) The output of each agent is constrained. Therefore, this paper presents an improved tan-type NM method to deal with the time-varying output constraints problem, and a partition algorithm is employed to implement bipartite consensus tracking control based on the unbalanced communication topology graph. Meanwhile, the nonsingular finite-time control strategy effectively improves the convergence of the studied nonlinear MASs. In addition, the system model and backstepping technology used in this paper are general and practical.
科研通智能强力驱动
Strongly Powered by AbleSci AI