摘要
研究了非线性系统的事件触发控制问题。首先,构建性能指标函数,基于贝尔曼最优准则,给出基于时间的最优控制器形式;其次,为了有效降低计算负担,提升信息利用率,引入事件触发采样机制;接着,基于事件触发采样瞬间系统状态,设计事件触发最优控制器;然后,为了获得事件触发哈密顿方程解析解,构建评价网络,设计权值更新律在线学习控制策略;最后,应用于倒立摆系统验证所提算法的有效性。
This paper studies the problem of event-triggered control for nonlinear system.Firstly,the performance index function is constructed and the optimal controller form based on time is given based on the Behrman optimal principle.Secondly,in order to reduce the computational burden and improve the utilization rate of information,the event-triggered sampling mechanism is introduced.Subsequently,based on the event-triggered sampling instantaneous system state,the event-triggered optimal controller is designed.Then,in order to obtain the analytical solution of the event-triggered Hamilton-Jacobi-Bellman equation,the evaluation network is constructed and the online learning control strategy of weight updating law is designed.Finally,the proposed algorithm is applied to torsional pendulum system to show its effectiveness.
作者
田辈辈
刘奇
TIAN Beibei;LIU Qi(College of Mechanical and Electrical Engineering,Jiaozuo University,Jiaozuo 454000,China)
出处
《机械工程师》
2023年第7期18-20,24,共4页
Mechanical Engineer
关键词
事件触发
神经网络
最优控制
倒立摆
event-triggered
neural network
optimal control
torsional pendulum
