Autotuning algorithm of particle swarm PID parameter based on D-Tent chaotic model  

作　　者：Min Zhu Chunling Yang Weiliang Li 

机构地区：[1]School of Electrical Engineering and Automation,Harbin Institute of Technology [2]China FAW Group Corporation R&D Center

出　　处：《Journal of Systems Engineering and Electronics》2013年第5期828-837,共10页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(61301011);the Fundamental Research Funds for the Central Universities(HIT.NSRIF.2012010);the China Postdoctoral Science Foundation(2013M540279);the Heilongjiang Postdoctoral Financial Assistance(LBH-Z11157)

摘　　要：An improved particle swarm algorithm based on the D-Tent chaotic model is put forward aiming at the standard particle swarm algorithm. The convergence rate of the late of proposed algorithm is improved by revising the inertia weight of global optimal particles and the introduction of D-Tent chaotic sequence. Through the test of typical function and the autotuning test of proportionalintegral-derivative （PID） parameter, finally a simulation is made to the servo control system of a permanent magnet synchronous motor （PMSM） under double-loop control of rotating speed and current by utilizing the chaotic particle swarm algorithm. Studies show that the proposed algorithm can reduce the iterative times and improve the convergence rate under the condition that the global optimal solution can be got.An improved particle swarm algorithm based on the D-Tent chaotic model is put forward aiming at the standard particle swarm algorithm. The convergence rate of the late of proposed algorithm is improved by revising the inertia weight of global optimal particles and the introduction of D-Tent chaotic sequence. Through the test of typical function and the autotuning test of proportionalintegral-derivative （PID） parameter, finally a simulation is made to the servo control system of a permanent magnet synchronous motor （PMSM） under double-loop control of rotating speed and current by utilizing the chaotic particle swarm algorithm. Studies show that the proposed algorithm can reduce the iterative times and improve the convergence rate under the condition that the global optimal solution can be got.

关 键 词：D-Tent particle swarm proportional-integral- derivative （PID） parameter optimization. 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] TM341[自动化与计算机技术—控制科学与工程]