电机与控制应用
電機與控製應用
전궤여공제응용
ELECTRIC MACHINES & CONTROL APPLICATION
2014年
11期
14-17,22
,共5页
无刷直流电机%模糊控制%自适应PID控制%优化算法
無刷直流電機%模糊控製%自適應PID控製%優化算法
무쇄직류전궤%모호공제%자괄응PID공제%우화산법
brushless DC motor%fuzzy control%adaptive PID control%optimization algorithm
针对直流调速系统采用传统PID控制方案存在精度低、抗干扰能力差等缺点,将PID控制、模糊控制和微粒群算法相结合,设计双闭环直流调速系统优化控制方案,改善直流系统的调速性能。电流内环采用电流滞环控制,转速外环分别采用传统PID控制器、自适应模糊PID控制器和微粒群优化的自适应模糊PID模糊控制器。在空载和扰动情况下,分析转速外环对双闭环无刷直流调速系统控制效果的影响。在MATLAB/Simulink中构建了双闭环无刷直流电机调速系统仿真模型,并对其进行仿真分析。仿真结果表明,无刷直流电机调速系统采用粒子群优化的自适应模糊PID控制器具有最优的动、静态性能和抗干扰能力。
針對直流調速繫統採用傳統PID控製方案存在精度低、抗榦擾能力差等缺點,將PID控製、模糊控製和微粒群算法相結閤,設計雙閉環直流調速繫統優化控製方案,改善直流繫統的調速性能。電流內環採用電流滯環控製,轉速外環分彆採用傳統PID控製器、自適應模糊PID控製器和微粒群優化的自適應模糊PID模糊控製器。在空載和擾動情況下,分析轉速外環對雙閉環無刷直流調速繫統控製效果的影響。在MATLAB/Simulink中構建瞭雙閉環無刷直流電機調速繫統倣真模型,併對其進行倣真分析。倣真結果錶明,無刷直流電機調速繫統採用粒子群優化的自適應模糊PID控製器具有最優的動、靜態性能和抗榦擾能力。
침대직류조속계통채용전통PID공제방안존재정도저、항간우능력차등결점,장PID공제、모호공제화미립군산법상결합,설계쌍폐배직류조속계통우화공제방안,개선직류계통적조속성능。전류내배채용전류체배공제,전속외배분별채용전통PID공제기、자괄응모호PID공제기화미립군우화적자괄응모호PID모호공제기。재공재화우동정황하,분석전속외배대쌍폐배무쇄직류조속계통공제효과적영향。재MATLAB/Simulink중구건료쌍폐배무쇄직류전궤조속계통방진모형,병대기진행방진분석。방진결과표명,무쇄직류전궤조속계통채용입자군우화적자괄응모호PID공제기구유최우적동、정태성능화항간우능력。
Considering the traditional PID control of DC motor speed regulating system has low precision, poor anti-interference ability, adouble loop DC speed control system was proposed for the design scheme, and BLDCM as the controlled object. In order to improve the dynamic performance of BLDCM speed control system, PID control is combined with fuzzy control and particle swarm optimization algorithm. Besides, the inner current loop adopts current hysteresis control. The speed outer ring adopts traditional PID controller, adaptive fuzzy PID controller and the particle swarm optimization of adaptive fuzzy PID controller. Finally, in the no-load and disturbance conditions, the paper analyzed the control effect of speed outer ring on BLDCM. And in MATLAB/Simulink, a simulation model was builded and analyzed. The simulation results show that, in the three kinds of control methods, the control system adopting the adaptive fuzzy PID controller based on particle swarm optimization has the best dynamic, static performance and anti-interference ability.