CAJ | 학술논문

对人工免疫算法、协同进化算法和粒子群算法三者相结合的免疫协同粒子群优化算法（ ICPSO ）进行改进，提出了一种适用于异步电动机参数辨识的ICPSO算法，并在传统的矢量控制系统基础上，运用该算法在线辨识出异步电动机参数，实时调整解耦控制器、磁链观测器和PI调节器参数，实现参数自适应，设计了基于ICPSO算法的异步电动机矢量控制系统。仿真结果表明，与传统的矢量控制系统相比，所设计的系统受电机参数变化影响较小，在磁链观测准确性、电机转速跟踪性和电磁转矩稳定性等方面有所改善。
대인공면역산법、협동진화산법화입자군산법삼자상결합적면역협동입자군우화산법（ ICPSO ）진행개진，제출료일충괄용우이보전동궤삼수변식적ICPSO산법，병재전통적시량공제계통기출상，운용해산법재선변식출이보전동궤삼수，실시조정해우공제기、자련관측기화PI조절기삼수，실현삼수자괄응，설계료기우ICPSO산법적이보전동궤시량공제계통。방진결과표명，여전통적시량공제계통상비，소설계적계통수전궤삼수변화영향교소，재자련관측준학성、전궤전속근종성화전자전구은정성등방면유소개선。
An improved immune co-evolutionary particle swarm optimization ( ICPSO) algorithm was proposed .It was the combination of artificial immune algorithm , co-evolutionary algorithm and particle swarm algorithm .Based on original vector control system , the online induction motor parameters were identified by the ICPSO algorithm .The parameters of the flux observa-tion, the decoupling controller and the PI controllers were then adjusted .Furthermore, a novel vector control system with parame-ters identification based on the ICPSO algorithm was designed .The simulation results show that compared with the original vector control system , the designed system preforms better in flux observation , speed tracking and torque control .