首页|输入死区和全状态约束下不确定非线性系统的快速稳定事件触发控制

输入死区和全状态约束下不确定非线性系统的快速稳定事件触发控制

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在实际工业系统中普遍存在输入死区、全状态约束等不可忽视的问题，其对系统的性能造成较大的影响，甚至可能会导致系统不稳定。为了克服上述问题，针对一类不确定非线性系统，提出一种快速收敛的自适应神经网络事件触发控制方法。首先，将障碍Lyapunov函数引入到反步控制框架中，采用径向基函数神经网络逼近未知非线性函数，同时设计自适应事件触发机制对输入死区进行动态补偿，通过减少控制信号的更新频率来减轻系统的通信负担，并保证系统所有状态不违反预定义的约束区间。在此基础上，引入快速有限时间稳定理论，在有限时间内能够保证闭环系统所有信号的有界性以及跟踪误差快速收敛到有界的紧集内。最后，通过两个仿真算例验证所提出控制方法的有效性。
Fast stability event-triggered control for uncertain nonlinear systems with input dead-zone and full-state constraints
Many problems can not be ignored in practical industrial systems,such as input dead-zone and full-state constraints,which have a significant impact on the performance of the system and may even lead to system instability.To overcome the above problems,this paper proposes a fast convergent adaptive neural network event-triggered control strategy for a class of uncertain nonlinear systems.First of all,the barrier Lyapunov function is introduced into the backstepping control framework and the radial basis function neural networks approximate the unknown nonlinear function.At the same time,an adaptive event triggering mechanism is designed to dynamically compensate for the input dead-zone.By reducing the update frequency of the control signal,the communication burden of the system is reduced,and all states of the system do not violate the predefined constraint interval.On this basis,the theory of fast finite-time stability is introduced,which can guarantee the boundedness of all signals in the closed-loop system in finite time and the tracking error quickly converges to the bounded compact set.Finally,the effectiveness of the control strategy is verified by two simulation examples.

fast finite-time stabilityinput dead-zonefull-state constraintsevent-triggered mechanismbarrier Lyapunov functionsnonlinear systems

王建晖、杜泳萍、邹涛、刘治、岳夏

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广州大学机械与电气工程学院,广州 510006

广东工业大学自动化学院,广州 510006

快速有限时间稳定 输入死区 全状态约束 事件触发机制 障碍Lyapunov函数 非线性系统

国家自然科学基金项目国家自然科学基金项目广东省自然科学基金项目广州市科技计划项目广州羊城学者项目

52171331522750972019A1515110995202002030286202235199

2024

10.13195/j.kzyjc.2022.1132

控制与决策
东北大学

控制与决策

CSTPCD北大核心
影响因子：1.227
ISSN：1001-0920
年,卷(期)：2024.39(2)
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