학술논문
Robust Admittance Control of Optimized Robot–Environment Interaction Using Reference Adaptation
Document Type
Periodical
Author
Source
IEEE Transactions on Neural Networks and Learning Systems IEEE Trans. Neural Netw. Learning Syst. Neural Networks and Learning Systems, IEEE Transactions on. 34(9):5804-5815 Sep, 2023
Subject
Language
ISSN
2162-237X
2162-2388
2162-2388
Abstract
In this article, a robust control scheme is proposed for robots to achieve an optimal performance in the process of interacting with external forces from environments. The environmental dynamics are defined as a linear model, and the interaction performance is evaluated by a defined cost function, which is composed of trajectory errors and force regulation. Based on admittance control, the reference adaptation method is used to minimize the cost function and achieve the optimal interaction performance. To make the trajectory tracking controller robust to the unknown disturbance of internal system dynamics, an auxiliary system is defined and the approximation optimal controller is designed. Experiments on the Baxter robot are conducted to verify the effectiveness of the proposed method.