永磁同步电机的神经网络离散位置跟踪控制
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摘要
针对永磁同步电动机参数不确定及负载扰动问题,本文基于自适应和反步法技术,设计了一种永磁同步电动机离散位置跟踪控制方法。利用欧拉公式得到同步电动机驱动系统的离散数学模型,采用动态面技术,引入低通一阶滤波器对虚拟控制函数进行滤波,解决了"计算爆炸"问题;运用神经网络逼近永磁同步电动机系统中存在的未知非线性项,并将神经网络和反步法相结合,构造离散动态面位置跟踪控制器,同时对其进行稳定性分析,最后通过仿真实验分析验证了该方法的有效性。仿真结果表明,本文设计的离散控制器能够有效跟踪给定信号,实现了对永磁同步电动机良好的位置跟踪控制效果。该控制方法解决了参数不确定性以及负载扰动问题,具有一定的理论意义和实际应用价值。
For the problems of parameter uncertainties and external load disturbance of permanent magnet synchronous motors(PMSMs),the discrete position tracking control method combined with RBF neural networks,dynamic surface technology and backstepping is presented in this paper.The discrete-time mathematical model of the synchronous motor drive system is obtained by the Euler formula.And the stability of the discrete position tracking controllers constructed based on the dynamic surface technology is analyzed in this paper.The simulation is run to verify the validity of the control method.The results show that the discrete position tracking controllers can effectively track the given signal and achieve position tracking control effect for PMSMs.The control method can solve the problems of parameter uncertainties and external load disturbance,which has certain theoretical meaning and practical application value.
For the problems of parameter uncertainties and external load disturbance of permanent magnet synchronous motors(PMSMs),the discrete position tracking control method combined with RBF neural networks,dynamic surface technology and backstepping is presented in this paper.The discrete-time mathematical model of the synchronous motor drive system is obtained by the Euler formula.And the stability of the discrete position tracking controllers constructed based on the dynamic surface technology is analyzed in this paper.The simulation is run to verify the validity of the control method.The results show that the discrete position tracking controllers can effectively track the given signal and achieve position tracking control effect for PMSMs.The control method can solve the problems of parameter uncertainties and external load disturbance,which has certain theoretical meaning and practical application value.
引文
[1]于金鹏,陈兵,于海生,等.基于自适应模糊反步法的永磁同步电机位置跟踪控制[J].控制与决策,2010,25(10):1547-1551.
[2]Zhang Y,Akujuobi C M,Ali W H,et al.Load Disturbance Resistance Speed Controller Design for PMSM[J].IEEE Transactions on Industrial Electronics,2006,53(4):1198-1208.
[3]于金鹏,于海生,林崇.考虑铁损的异步电动机模糊自适应命令滤波反步控制[J].控制与决策,2016,31(12):2189-2194.
[4]Farrell J A,Polycarpou M,Sharma M,et al.Command Filtered Backstepping[J].IEEE Transactions on Automatic Control,2009,54(6):1391-1395.
[5]沈艳霞,林瑾,纪志成.神经网络磁链估计的感应电机反步法研究[J].控制与决策,2006,21(7):833-836.
[6]李建立,于海生.永磁同步电机驱动系统的反步与无源协调控制[J].电机与控制应用,2018,45(1):23-29.
[7]冯引安,祝小平,周洲.弹性飞翼无人机自适应反步终端滑模姿态控制[J].华中科技大学学报:自然科学版,2018,46(3):42-47.
[8]Shang W,Zhao S,Shen Y,et al.A Sliding Mode Flux-Linkage Controller with Integral Compensation for Switched Reluctance Motor[J].IEEE Transactions on Magnetics,2009,45(9):3322-3328.
[9]杨永强.基于滑模控制的四旋翼无人机姿态跟踪研究[J].中国新技术新产品,2018(1下):125-127.
[10]于海生,赵克友,郭雷,等.基于端口受控哈密顿方法的MSM最大转矩/电流控制[J].中国电机工程学报,2006,26(8):82-87.
[11]Guo Y,Xi Z,Cheng D.Speed Regulation of Permanent Magnet Synchronous Motor via Feedback Dissipative Hamiltonian Realization[J].IET Control Theory&Applications,2007,1(1):281-290.
[12]Yu H S,Yu J P,Liu J,et al.Nonlinear Control of Induction Motors Based on State Error PCH And Energy-Shaping Principle[J].Nonlinear Dynamics,2013,72(1/2):49-59.
[13]Yu J,Shi P,Dong W,et al.Observer And Command Filter-Based Adaptive Fuzzy Output Feedback Control of Uncertain Nonlinear Systems[J].IEEE Transactions on Industrial Electronics,2015,62(9):5962-5970.
[14]付程,马玉梅,于金鹏,等.基于神经网络的异步电动机自适应动态面控制[J].青岛大学学报:工程技术版,2017,32(2):38-45.
[15]Yu J P,Shi P,Yu H S,et al.Approximation-Based Discrete-Time Adaptive Position Tracking Control for Interior Permanent Magnet Synchronous Motors[J].IEEE Transactions on Cybernetics,2015,45(7):1363-1371.
[16]周真诚,马玉梅,于金鹏,等.异步电动机的动态面模糊离散速度跟踪控制[J].青岛大学学报:工程技术版,2016,31(2):47-52.
[17]Yu J P,Shi P,Dong W J,et al.Neural Network-Based Adaptive Dynamic Surface Control for Permanent Magnet Synchronous Motors[J].IEEE Transactions on Neural Networks and Learning Systems,2015,26(3):640-645.
[18]Yu J P,Chen B,Yu H S,et al.Adaptive Fuzzy Tracking Control for the Chaotic Permanent Magnet Synchronous Motor Drive System via Backstepping[J].Nonlinear Analysis:Real World Applications,2011,12(1):671-681.
[19]Wang D,Huang J.Neural Network-Based Adaptive Dynamic Surface Control for a Class of Uncertain Nonlinear Systems in Strict Feedback Form[J].IEEE Transactions on Neural Networks,2005,16(1):195-202.
[20]Yu J P,Chen B,Yu H S,et al.Neural Networks-Based Command Filtering Control of Nonlinear Systems with Uncertain Disturbance[J].Information Sciences,2018,426:50-60.
[21]邓敏强,傅行军.基于RBF神经网络的汽封动力特性系数计算模型[J].汽轮机技术,2018,60(1):59-62.
[2]Zhang Y,Akujuobi C M,Ali W H,et al.Load Disturbance Resistance Speed Controller Design for PMSM[J].IEEE Transactions on Industrial Electronics,2006,53(4):1198-1208.
[3]于金鹏,于海生,林崇.考虑铁损的异步电动机模糊自适应命令滤波反步控制[J].控制与决策,2016,31(12):2189-2194.
[4]Farrell J A,Polycarpou M,Sharma M,et al.Command Filtered Backstepping[J].IEEE Transactions on Automatic Control,2009,54(6):1391-1395.
[5]沈艳霞,林瑾,纪志成.神经网络磁链估计的感应电机反步法研究[J].控制与决策,2006,21(7):833-836.
[6]李建立,于海生.永磁同步电机驱动系统的反步与无源协调控制[J].电机与控制应用,2018,45(1):23-29.
[7]冯引安,祝小平,周洲.弹性飞翼无人机自适应反步终端滑模姿态控制[J].华中科技大学学报:自然科学版,2018,46(3):42-47.
[8]Shang W,Zhao S,Shen Y,et al.A Sliding Mode Flux-Linkage Controller with Integral Compensation for Switched Reluctance Motor[J].IEEE Transactions on Magnetics,2009,45(9):3322-3328.
[9]杨永强.基于滑模控制的四旋翼无人机姿态跟踪研究[J].中国新技术新产品,2018(1下):125-127.
[10]于海生,赵克友,郭雷,等.基于端口受控哈密顿方法的MSM最大转矩/电流控制[J].中国电机工程学报,2006,26(8):82-87.
[11]Guo Y,Xi Z,Cheng D.Speed Regulation of Permanent Magnet Synchronous Motor via Feedback Dissipative Hamiltonian Realization[J].IET Control Theory&Applications,2007,1(1):281-290.
[12]Yu H S,Yu J P,Liu J,et al.Nonlinear Control of Induction Motors Based on State Error PCH And Energy-Shaping Principle[J].Nonlinear Dynamics,2013,72(1/2):49-59.
[13]Yu J,Shi P,Dong W,et al.Observer And Command Filter-Based Adaptive Fuzzy Output Feedback Control of Uncertain Nonlinear Systems[J].IEEE Transactions on Industrial Electronics,2015,62(9):5962-5970.
[14]付程,马玉梅,于金鹏,等.基于神经网络的异步电动机自适应动态面控制[J].青岛大学学报:工程技术版,2017,32(2):38-45.
[15]Yu J P,Shi P,Yu H S,et al.Approximation-Based Discrete-Time Adaptive Position Tracking Control for Interior Permanent Magnet Synchronous Motors[J].IEEE Transactions on Cybernetics,2015,45(7):1363-1371.
[16]周真诚,马玉梅,于金鹏,等.异步电动机的动态面模糊离散速度跟踪控制[J].青岛大学学报:工程技术版,2016,31(2):47-52.
[17]Yu J P,Shi P,Dong W J,et al.Neural Network-Based Adaptive Dynamic Surface Control for Permanent Magnet Synchronous Motors[J].IEEE Transactions on Neural Networks and Learning Systems,2015,26(3):640-645.
[18]Yu J P,Chen B,Yu H S,et al.Adaptive Fuzzy Tracking Control for the Chaotic Permanent Magnet Synchronous Motor Drive System via Backstepping[J].Nonlinear Analysis:Real World Applications,2011,12(1):671-681.
[19]Wang D,Huang J.Neural Network-Based Adaptive Dynamic Surface Control for a Class of Uncertain Nonlinear Systems in Strict Feedback Form[J].IEEE Transactions on Neural Networks,2005,16(1):195-202.
[20]Yu J P,Chen B,Yu H S,et al.Neural Networks-Based Command Filtering Control of Nonlinear Systems with Uncertain Disturbance[J].Information Sciences,2018,426:50-60.
[21]邓敏强,傅行军.基于RBF神经网络的汽封动力特性系数计算模型[J].汽轮机技术,2018,60(1):59-62.