Adaptive dynamic programming-based controller with admittance adaptation for robot–environment interaction. (5th June 2020)

• Record Type: Journal Article
• Authors: Zhan, Hong; Huang, Dianye; Chen, Zhaopeng; Wang, Min; Yang, Chenguang
• Is Part Of: International journal of advanced robotic systems. Volume 17:Number 3(2020:May/Jun.)
• Publication Date: 2020-06-05
• Subjects: Adaptive dynamic programming -- admittance adaptation -- neural network -- optimal control -- robot–environment interaction; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881420924610
• Languages: English
• ISSNs: 1729-8806

Abstract

The problem of optimal tracking control for robot–environment interaction is studied in this article. The environment is regarded as a linear system and an admittance control with iterative linear quadratic regulator method is obtained to guarantee the compliant behaviour. Meanwhile, an adaptive dynamic programming-based controller is proposed. Under adaptive dynamic programming frame, the critic network is performed with radial basis function neural network to approximate the optimal cost, and the neural network weight updating law is incorporated with an additional stabilizing term to eliminate the requirement for the initial admissible control. The stability of the system is proved by Lyapunov theorem. The simulation results demonstrate the effectiveness of the proposed control scheme.