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Seeker optimization algorithm for optimal control of manipulator

Chunchao Chen, Jinsong Li, Jun Luo, Shaorong Xie, Hengyu Li

Industrial Robot

ISSN: 0143-991X

Article publication date: 17 October 2016

534

Abstract

Purpose

This paper aims to improve the adaptability and control performance of the controller, a proposed seeker optimization algorithm (SOA) is introduced to optimize the controller parameters of a robot manipulator.

Design/methodology/approach

In this paper, a traditional proportional integral derivative (PID) controller and a fuzzy logic controller are integrated to form a fuzzy PID (FPID) controller. The SOA, as a novel algorithm, is used for optimizing the controller parameters offline. There is a performance comparison in terms of FPID optimization about the SOA, the genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). The DC motor model and the experimental platform are used to test the performance of the optimized controller.

Findings

Compared with GA, PSO and ACO, this novel optimization algorithm can enhance the control accuracy of the system. The optimized parameters ensure a system with faster response speed and better robustness.

Originality/value

A simplified FPID controller structure is constructed and a novel SOA method for FPID controller is presented. In this paper, the SOA is applied on the controller of 5-DOF manipulator, and the validation of controllers is tested by experiments.

Keywords

Acknowledgements

This work is supported by the National Natural Science Foundation of China (No.61305106) and the Key Projects of the National Natural Science Foundation of China (No. 61233010). The supports are gratefully acknowledged.

Citation

Chen, C., Li, J., Luo, J., Xie, S. and Li, H. (2016), "Seeker optimization algorithm for optimal control of manipulator", Industrial Robot, Vol. 43 No. 6, pp. 677-686. https://doi.org/10.1108/IR-12-2015-0225

Publisher

:

Emerald Group Publishing Limited

Copyright © 2016, Emerald Group Publishing Limited

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