- 【SCI3区】Event-triggered optimal interaction control of the MRM system under the complex multi-task constraints: design and experiments
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- 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 the Franklin Institute
- 项目来源：国家自然科学基金项目
- 关键字：modular robot manipulators, event-triggered mechanism, adaptive dynamic programming algorithm, optimal interaction control, collision detection, neural network
- 摘要：The main challenges of modular robot manipulators (MRMs) with the environmental constraints include the avoidance of catastrophic collision and the precious contacting in the whole interaction process. Consequently, an event-triggered optimal interaction control method of MRMs under the complex multi-task constraints is presented in this paper. Firstly, on the basis of the joint torque feedback (JTF) technique, the dynamic model of constrained MRM subsystem is established. Secondly, the sensorless-based decentralized nonlinear disturbance observer (NDOB) is proposed to detect and identify the sudden external collision for each joint. Then, the performance index function is improved to achieve the interaction control, which contains the fusion state variable function, the influence of external collision, the known model term, and the estimation of model uncertainties through the radial basis function neural network (RBFNN) identifier. Further, based on event-triggered mechanism and adaptive dynamic programming (ADP) algorithm, the approximate event-triggered optimal interaction control strategy is acquired by the critic neural network (NN). Next, the closed-loop MRM system is demonstrated to be uniformly ultimately bounded (UUB) through the Lyapunov stability theorem. Finally, the experiments are achieved effectively for each joint on the platform, such that the feasibility and universality of the proposed interaction control approach are testified by the experimental results.
- 合写作者：姚锡明,马冰,马冰
- 第一作者：李元春
- 论文类型：期刊论文
- 页面范围：1
- 是否译文：否
- 发表时间：2022-12-05
