Parameters optimization of mechanical arm PID controllers based on CLPSO algorithm

Author

Li Xiaolong ; Chen Yanjie ; Yu Xiao

Author_Institution

Sch. of Electr. Eng., Southwest Jiaotong Univ., Chengdu, China

fYear

2011

fDate

3-5 Aug. 2011

Firstpage

56

Lastpage

60

Abstract

This paper presents an improved algorithm named Comprehensive Learning Particle Swarm Optimization (CLPSO). CLPSO utilizes a novel learning strategy which has achieved the goal to accelerate the convergence of the classic PSO. And CLPSO algorithm is more effective to optimize PID controller´s parameters than empirical tuning methods and classic PSO. The simulation results show its better performance than traditional ways in the PID parameters optimization for PID controllers in mechanical arm system.

Keywords

control system synthesis; learning (artificial intelligence); manipulators; particle swarm optimisation; three-term control; CLPSO algorithm; comprehensive learning particle swarm optimization; empirical tuning methods; learning strategy; mechanical arm PID controllers; parameter optimization; Algorithm design and analysis; Educational institutions; Joints; Mathematical model; Optimization; Particle swarm optimization; Tuning; CLPSO; PID; PSO; mechanical arm; parameters optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science & Education (ICCSE), 2011 6th International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-9717-1

Type

conf

DOI

10.1109/ICCSE.2011.6028584

Filename

6028584