- 【SCI3区通讯作者周帆】Event-triggered-based decentralized optimal control of modular robot manipulators using RNN identifier
- 点击次数：
- 所属单位：电气与电子工程学院
- 教研室：自动化
- 发表刊物：Journal of Intelligent & Robotic Systems
- 项目来源：国家自然科学基金项目
- 关键字：Modular robot manipulators; Joint torque feedback technique; Neuro-dynamic programming; Event-triggered mechanism; Decentralized tracking control
- 摘要：In this paper, an event-triggered-based decentralized tracking control method is proposed for modular robot manipulators (MRMs) using a recurrent neural network (RNN) and neuro-dynamic programming (NDP). The joint torque feedback (JTF) technique is introduced to model the MRM subsystems. The cost function of each subsystem consists of a tracking error fusion function and a term summarizing the RNN identifier errors. The event-triggered Hamiltonian-Jacobi-Bellman (ETHJB) equation is solved by constructing a critic neural network using NDP, and a decentralized optimal tracking control policy under the event-triggered framework can be obtained. The closed-loop MRM system is shown to be uniformly ultimately bounded under the Lyapunov stability theorem. Finally, the experimental results verify that the proposed control method is superior to the time-triggered optimal control policy and the observer-critic based event-triggered optimal control policy proposed in the previous work of the author.
- 合写作者：潘强,马冰,安天骄,周帆,周帆
- 第一作者：李元春
- 论文类型：期刊论文
- 卷号：106
- 期号：3
- 页面范围：1
- ISSN号：0921-0296
- 是否译文：否
- 发表时间：2022-10-20
