基于GSO-BFA算法的PMSM自适应模糊滑模控制

Research on Speed Sensorless PMSM With Adaptive Fuzzy SMC Based on GSO-BFA

为研究永磁同步电机(PMSM)在无速度传感器工况下的速度跟踪估计,以PMSM的工作原理为基础,建立内埋式PMSM的数学模型。基于自适应模糊微分积分滑模(AFDI-SMC)鲁棒性强的优点,提出了在萤火虫-细菌觅食(GSO-BFA)融合算法优化滑模控制器参数条件下采用旋转高频电压注入法对电机转速进行估计的无速度传感器控制方案,并分析了电机在高、低速运行时特点。实验结果表明,采用GSO-BFA融合算法优化滑模控制器参数并结合高频电压注入法的自适应模糊滑模控制系统在高速(2000 r/min)负载工况下的绝对误差为60 r/min,转速相对误差为3%,稳定运行时转子位置最大误差约为4°电角度(合2°机械角度);低速(50 r/min)负载工况下的绝对误差为8 r/min,转速相对误差为16%,稳定运行时转子位置最大误差约为5°电角度(合2.5°机械角度)。

Based on the principle of PMSM, a mathematical model of embedded PMSM was established for the study of speed tracking estimates of PMSM without speed sensor. The speed sensorless control scheme, which adopted rotating high frequency voltage injection method to estimate the speed of the motor, was pro- posed with fusion algorithms of glowworm swarm optimization and bacterial foraging algorithm （GSO-BFA） on the basis of robust advantages of adaptive fuzzy differential and integral sliding mode control （AFDI- SMC ）, and its working characters at both high and low speed were also analyzed. Experimental results illus- trate that the relative error is approximately 3% （60 r/rain） at the loaded high speed （2000 r/rain） and 16% （8 r/min） at the loaded low speed （50 r/min） ; the absolute position error of rotor at stable condition is 4 electrical degrees （2 mechanical degrees） and 5 electrical degrees （2. 5 mechanical degrees） for each.