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http://dx.doi.org/10.6109/jkiice.2016.20.9.1679

An Adaptive PD Control Method for Mobile Robots Using Gradient Descent Learning  

Choi, Young-Kiu (Department of Electrical Engineering, Pusan National University)
Park, Jin-Hyun (Dept. of Mechatronics Engineering, Kyeognam National Univ. of Science and Technology)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.20, no.9, 2016 , pp. 1679-1687 More about this Journal
Abstract
Mobile robots are effectively used in industrial fields that require flexible manufacturing systems. Mobile robots have to move with mechanical loads such as product parts along the specified paths, and are usually equipped with kinematic controllers. When the loads and nonlinear frictions are too high, satisfactory control performances can not be expected with the kinematic controllers, so some dynamic controllers have been developed. Conventional dynamic controllers require the exact weights and locations of the loads; however, the loads are frequently changed and unknown so that the control performances of the conventional controllers are limited. This paper proposes an adaptive PD control method using gradient descent learning to have sufficient dynamic control performance for unknown loads. Simulation studies have been conducted for various load conditions to verify that the adaptive PD control method have much broader convergence region than the convention method.
Keywords
Mobile Robot; Dynamic Controller; Load Variation; Gradient Descent Learning; Adaptive Pd Control;
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