Affiliation:
1. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
2. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, China
Abstract
To overcome the problems of structural parametric uncertainty and cable transmission model complexity, a nonlinear controller based on time-delay estimation and fuzzy self-tuning is proposed. The unknown dynamics and disturbances are estimated by time delaying the state of motion immediately before. The control gains are self-tuned by a fuzzy controller, which can reduce the errors caused by system’s uncertainties and external disturbances. Compared with the conventional Proportional-derivative (PD) and time-delay control, the result shows that the proposed control scheme based on time-delay estimation can improve the joint trajectory tracking accuracy of cable-driven robot by significantly reducing the control gains. With the PD gains self-tuned by fuzzy strategy, the mean square errors of trajectory tracking are decreased approximately by 5–20% more than the conventional time-delay control with constant gains. In addition, the experimental result shows that the proposed method has an effective inhibitory effect on dead zone in cable-driven joints. Experiment performed on position tracking control of a 2-degree-of-freedom cable-driven robot is presented to illustrate that the controller has the advantages of simple and reliable structure, model-free, strong robustness, and high tracking accuracy.
Funder
China Postdoctoral Science Foundation
Subject
Artificial Intelligence,Computer Science Applications,Software
Cited by
7 articles.
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