基于云模型的改进粒子群PMSM参数辨识算法
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摘要
针对永磁同步电机传统参数辨识方法存在的缺陷,提出了一种基于云模型的改进粒子群参数辨识算法.该算法首先采用高频电压注入法建立高频电压方程,通过滤波处理获取高低频信号构建四阶满秩实时电机辨识模型;将云模型理论与粒子群算法相结合,采用正态云发生器对粒子进化变异操作建模,实现了自适应动态调节粒子的搜索范围,有效克服早熟收敛,保证了辨识参数为全局最优解.实验表明该辨识方法寻优能力强,搜索精度高,稳定性好,具有良好的动态性能.
Aiming at the defects of the traditional parameter identification method of permanent magnet synchronous motor,an improved particle swarm parameter identification algorithm is proposed based on cloud model.The high-frequency voltage equation is established by using high-frequency voltage injection method,obtaining high and low frequency signals through filter processing to construct a fourth-order full rank real-time motor identification model.Combining cloud model theory with particle swarm algorithm,the variation of particle is modeled by normal cloud generator to realize adaptive dynamic adjustment of particle search range,overcome premature convergence effectively and ensure the identification parameters of global optimal solutions.Simulation results show that this algorithm has excellent searching ability,high searching accuracy,good stability and good dynamic performance.
Aiming at the defects of the traditional parameter identification method of permanent magnet synchronous motor,an improved particle swarm parameter identification algorithm is proposed based on cloud model.The high-frequency voltage equation is established by using high-frequency voltage injection method,obtaining high and low frequency signals through filter processing to construct a fourth-order full rank real-time motor identification model.Combining cloud model theory with particle swarm algorithm,the variation of particle is modeled by normal cloud generator to realize adaptive dynamic adjustment of particle search range,overcome premature convergence effectively and ensure the identification parameters of global optimal solutions.Simulation results show that this algorithm has excellent searching ability,high searching accuracy,good stability and good dynamic performance.
引文
[1]Rahman M A,Vilathgamuwa D M,Uddinand M N,et al.Nonlinear control of interior permanent magnet synchronous motor[J].IEEE Transactions on Industry Applications,2003,39(2):408-416.
[2]杨立永,张云龙,陈智刚,等.基于参数辨识的PMSM电流环在线自适应控制方法[J].电工技术学报,2012,27(3):86-91.
[3]史宇超,孙凯,马鸿雁,等.内埋式永磁同步电机永磁磁链的在线辨识[J].电工技术学报,2011,26(9):48-53.
[4]陈浈斐,李志新,马宏忠.表面-内置混合式永磁同步电机性能与转子参数影响[J].电机与控制学报,2017,21(2):63-69.
[5]魏海峰,韦汉培,张懿.基于扩张状态观测器的永磁同步电机PWM电流预测控制[J].控制与决策,2018,33(2):351-355.
[6]HONGWEI GE,LIANG SUN,GUOZHEN TAN,et al.Cooperative Hierarchical PSO With Two Stage Variable Interaction Reconstruction for Large Scale Optimization[J].IEEE Transactions on Cybernetics,2017,9(47):2809-2823.
[7]HONGGUI HAN,WEI LU,JUNFEI QIAO.An Adaptive Multiobjective Particle Swarm Optimization Based on Multiple Adaptive Methods[J].IEEE Transactions on Cybernetics,2017,9(47):2754-2767.
[8]林国汉,章兢,刘朝华,等.改进综合学习粒子群算法的PMSM参数辨识[J].电机与控制学报,2015,19(1):51-57.
[9]BONYADI M R,LI X,MICHALEWICZ Z.A hybrid particle swarm with velocity mutation for constraint optimization problems[C].Proc.of the Genetic and Evolutionary Computation Conference,2013.
[10]傅小利,顾红兵,陈国呈,等.基于柯西变异粒子群算法的永磁同步电机参数辨识[J].电工技术学报,2014,29(5):127-131.
[11]LIU KAN,ZHANG QIAO,CHEN JINTAO,et al.Online multiparameter estimation of nonsalient-pole PM synchronous machines with temperature variation Tracking[J].IEEE Transactions on Industaial Elec-tronics,2011,58(5):1776-1788.
[12]李德毅,孟海军,史雪梅.隶属云和隶属云发生器[J].计算机研究与发展,1995,32(6):15-20.
[13]陈振锋,钟彦儒,李洁.感应电机参数辨识三种智能算法的比较[J].电机与控制学报,2010,14(11):7-12.
[2]杨立永,张云龙,陈智刚,等.基于参数辨识的PMSM电流环在线自适应控制方法[J].电工技术学报,2012,27(3):86-91.
[3]史宇超,孙凯,马鸿雁,等.内埋式永磁同步电机永磁磁链的在线辨识[J].电工技术学报,2011,26(9):48-53.
[4]陈浈斐,李志新,马宏忠.表面-内置混合式永磁同步电机性能与转子参数影响[J].电机与控制学报,2017,21(2):63-69.
[5]魏海峰,韦汉培,张懿.基于扩张状态观测器的永磁同步电机PWM电流预测控制[J].控制与决策,2018,33(2):351-355.
[6]HONGWEI GE,LIANG SUN,GUOZHEN TAN,et al.Cooperative Hierarchical PSO With Two Stage Variable Interaction Reconstruction for Large Scale Optimization[J].IEEE Transactions on Cybernetics,2017,9(47):2809-2823.
[7]HONGGUI HAN,WEI LU,JUNFEI QIAO.An Adaptive Multiobjective Particle Swarm Optimization Based on Multiple Adaptive Methods[J].IEEE Transactions on Cybernetics,2017,9(47):2754-2767.
[8]林国汉,章兢,刘朝华,等.改进综合学习粒子群算法的PMSM参数辨识[J].电机与控制学报,2015,19(1):51-57.
[9]BONYADI M R,LI X,MICHALEWICZ Z.A hybrid particle swarm with velocity mutation for constraint optimization problems[C].Proc.of the Genetic and Evolutionary Computation Conference,2013.
[10]傅小利,顾红兵,陈国呈,等.基于柯西变异粒子群算法的永磁同步电机参数辨识[J].电工技术学报,2014,29(5):127-131.
[11]LIU KAN,ZHANG QIAO,CHEN JINTAO,et al.Online multiparameter estimation of nonsalient-pole PM synchronous machines with temperature variation Tracking[J].IEEE Transactions on Industaial Elec-tronics,2011,58(5):1776-1788.
[12]李德毅,孟海军,史雪梅.隶属云和隶属云发生器[J].计算机研究与发展,1995,32(6):15-20.
[13]陈振锋,钟彦儒,李洁.感应电机参数辨识三种智能算法的比较[J].电机与控制学报,2010,14(11):7-12.