非线性广义分数阶多智能体系统迭代学习趋同控制
首发时间:2024-07-25
摘要:针对一类含有扰动的非线性广义分数阶多智能体系统,研究其在不同通信拓扑协议下闭环型迭代学习一致性趋同跟踪问题。首先,基于分数阶微积分特性及广义的gronwall不等式,给出非线性广义分数阶多智能体系统在固定通信拓扑下一致性趋同误差收敛的充分条件。然后,将所得到的理论结果推广到通信拓扑随迭代变轴变化的情形,并分析了被控多智能体系统趋同跟踪误差的收敛特性。最后,通过两个数值仿真实例验证了所提闭环型迭代学习趋同控制协议的有效性。
关键词: 迭代学习控制 非线性广义分数阶多智能体系统 收敛性分析 趋同跟踪
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consensus tracking via iterative learning control for singular nonlinear fractional-order mass
abstract:for a class of nonlinear generalized fractional-order multi-agent systems with disturbances, the closed-loop -type iterative learning consensus tracking problem under different communication topology protocols is studied. firstly, based on the characteristics of fractional calculus and generalized gronwall inequality, a sufficient condition for the convergence of consensus error of nonlinear generalized fractional-order multi-agent systems under fixed communication topology is given. then, the obtained theoretical results are extended to the case where the communication topology changes with the iteration axis, and the convergence characteristics of the convergence tracking error of the controlled multi-agent system are analyzed. finally, the effectiveness of the proposed closed-loop -type iterative learning consensus control protocol is verified by two numerical simulation examples.
keywords: iterative learning control singular nonlinear fractional-order multi-agent systems (mass) convergence analysis consensus tracking
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