A Self-learning Nonlinear Variable Gain Proportional Derivative (PD) Controller in Robot Manipulators

Kiong, Loo Chu and Rajeswari, Mandava and Kiong, Wong Eng and Rao, M. V. C. (2004) A Self-learning Nonlinear Variable Gain Proportional Derivative (PD) Controller in Robot Manipulators. Pertanika Journal of Science & Technology, 12 (2). pp. 139-158. ISSN 0128-7680

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Abstract

This paper proposes a nonlinear variable gain Proportional-Derivative (PD) controller that exhibits self-constructing and self-learning capabilities. In this method, the conventional linear PD controller is augmented with a nonlinear variable PD gain control signal using a dynamic structural network. The dynamic structural network known as Growing Multi-Experts etwork grows in time by placing hidden nodes in regions of the state space visited by the system during operation. This results in a network that is "economic" in terms of network sileo The proposed approach enhances the adaptability of conventional PD controller while preserving its' linear structure. Based on the simulation study on variable load and friction compensation, the fast adaptation is shown to be able to compensate the non-linearity and the uncertainty in the robotic system.

Item Type:Article
Keyword:Nonlinear PD Controller, feedback error learning, dynamic structure neural network, friction compensation, variable load compensation
Publisher:Universiti Putra Malaysia Press
ID Code:3621
Deposited By: Nur Izyan Mohd Zaki
Deposited On:30 Nov 2009 07:22
Last Modified:27 May 2013 07:09

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