基于粒子群算法的永磁同步电机无传感器控制优化  

Optimization of PMSM Sensorless Control System Based on PSO Algorithm

作　　者：陈小龙[1] 

机构地区：[1]江阴职业技术学院,江苏江阴214405

出　　处：《组合机床与自动化加工技术》2014年第1期125-128,共4页Modular Machine Tool & Automatic Manufacturing Technique

摘　　要：针对确定噪声矩阵参数的困难性,将粒子群优化算法用于噪声矩阵参数的寻找。以电机转速的实际值和估计值的偏差绝对值对时间的积分为适应度函数,通过不断调整粒子在空间中的位置,最终寻找到使得适应度函数最小的粒子位置,从而得到使偏差最小的协方差矩阵。测试结果显示,经粒子群算法优化噪声矩阵参数后的系统,速度估计精度明显提高。优化后的电机实际速度波形脉动减小,调速更加平稳。Aiming at difficulty of determining the noise matrix parameter, PSO algorithm is applied to the optimization of noise parameter matrix, the fitness function is the time integral of the absolute value of the deviation between actual value and estimated value of the motor speed, the position of the particle, which makes the value of fitness function the smallest, is ultimately determined through constantly adjusting the position of the particle in the space, thereby computing matrix with the smallest deviation. The results show that the precision of speed estimation is obviously improved after noise matrix parameters of the system are optimized by PSO algorithm. And optimized waveform pulse of the motor speed diminishes, speed - governing is more stable.

关 键 词：粒子群算法 永磁同步电机 扩展卡尔曼滤波 无传感器控制 

分 类 号：TH39[机械工程—机械制造及自动化] TM351[电气工程—电机]