Design of PID Controller with Grey Particle Swarm Optimization Algorithm

• Main Authors: Kai-Min Chen, 陳凱旻
• Other Authors: Ming-Feng Yeh
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/30965058009270856368

碩士 === 龍華科技大學 === 電機工程系碩士班 === 100 === Based on grey relational analysis, this thesis proposes a grey particle swarm optimization (GPSO) algorithm in which both the inertia weight and acceleration coefficients are varying over the iterations. Besides, a mutation strategy is proposed to guide the global optimum of particles jump out of local optima and improve the accuracy of the global optimum and premature convergence to local optima drawback. The proposed GPSO is applied to solve the optimization problems of twelve unimodal and multimodal benchmark functions for demonstrating its search performance. Besides, the grey PSO algorithm is also applied to optimize the parameters of the proportional-integral-derivative (PID) controller. Simulation and experiment results demonstrate the search ability and control performance of the GPSO.