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面向永磁同步电机参数辨识的免疫完全学习型粒子群算法

, PP. 118-126

Keywords: 人工免疫系统,粒子群优化,完全学习,永磁同步电机,参数辨识

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Abstract:

实际工程中永磁同步电机系统是一种具有强非线性动态系统,常规方法难以得到高精度参数估计值。结合完全学习型粒子群的多模态优化性能及免疫机理局部收敛能力强的优势,研究了免疫完全学习型粒子群智能计算模型方法。将所提方法应用于永磁同步电机系统参数辨识与建模中,构建一种基于免疫完全学习型粒子群算法的永磁同步电机多参数辨识模型方法。实验结果表明所提算法具有高效收敛性能,基于该算法的永磁同步电机多参数辨识模型方法不需要依赖任何数据手册上的电机设计值,能同时辨识电机定子电阻,转子磁链,d-q轴电感等电磁参数,且能跟踪电磁参数变化。

References

[1]  Ooshima M A Chiba, Rahman A, et al. An improved control method of buried-type IPM bearingless motors considering magnetic saturation and magnetic pull variation[J]. IEEE Transactions on Energy Conversion, 2004, 19(3): 569-575.
[2]  Rahman M A, Vilathgamuwa D M, Uddin M N, et al. Nonlinear control of interior permanent magnet synchronous motor[J]. IEEE Transactions on Industry Applications, 2003, 39(2): 408-416.
[3]  Rashed M, Macconnell P F A, Stronach A F, et al. Senseless indirect-rotor-field-orientation speed control of a permanent-magnet synchronous motor with stator-resistance estimation[J]. IEEE Transaction on Industrial Application, 2007, 54(3): 1664-1675.
[4]  Reigosa D, Briz F, Garcia P, et al. Magnet temperature estimation in surface PM machines using high frequency signal injection[J]. IEEE Transactions on Industry Applications, 2010, 46(4): 1468-1475.
[5]  Ramakrishnan R, Islam R, Islam M, et al. Real time estimation of parameters for controlling and monitoring [C]. Proceedings of IEEE International Electric Machines and Drives Conference, Miami, USA, 2009:
[6]  Bolognani S, Tubiana L, Zigliotto M. Extended Kalman filter tuning in sensorless PMSM drives[J]. IEEE Transactions on Industry Applications, 2003, 39(6): 1741-1747.
[7]  Liu K, Zhang Q, Chen J T, et al. Online multiparameter estimation of nonsalient-pole PM synchronous machines with temperature variation tracking[J]. IEEE Transac- tions on Industrial Electronics, 2011, 58(5): 1776-1788.
[8]  Liu Z H, Zhang J, Zhou S W, et al. Co evolutionary particle swarm optimization using AIS and its application in multi-parameter estimation of PMSM [J]. IEEE Transactions on Cybernetics, 2013, 43(6): 1921-1935.
[9]  Liu L, Liu W X, David A Cartes. Permanent magnet synchronous motor parameter identification using particle swarm optimization[J]. International Journal of Computational Intelligence Research, 2008, 4(2): 211-218.
[10]  Liang J J, Qin A K, Suganthan P N, et al. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions[J]. IEEE Transactions on Evolutionary Computation, 2006, 10(3): 281-295.
[11]  Wu H, Geng J P, Jin R H, et al. An improved comprehensive learning particle swarm optimization and its application to the semiautomatic design of antennas[J]. IEEE Transactions on Antennas and Propagation, 2009, 57(10): 3018-3028.
[12]  王瑜, 李斌, 袁博. 混合SQP的基于完全学习的粒子群优化算法在电力系统中经济分配问题的应用[J]. 中国科学: 信息科学, 2010, 40(3): 403-411. Wang Yu, Li Bin, Yuan Bo. Hybrid comprehensive learning particle swarm optimization based on SQP and application in power system economic dispatch problem[J]. Chinese Science: Information, 2010, 40(3): 403-411.
[13]  Dasgupta D. Advances in artificial immune systems [J]. IEEE Computational Intelligence Magazine, 2006, 1(4): 40-49.
[14]  Eberhart R, Kennedy J A. A new optimizer using particleswarmtheory[C]. Proceeding of International Symposium on Micromachineand Human Science, Nagoya, Japan: IEEE, 1995: 39-43.
[15]  Ge H W, Sun L, Liang Y C, et al. An effective PSO and AIS-based hybrid intelligent algorithm for job- shop scheduling[J]. IEEE Transactions on Systems, Man, and Cybernetics, PartA, Systems and Humans, 2008, 38(2): 358-363.
[16]  刘朝华, 张英杰, 章兢, 等. 一种双态免疫微粒群算法[J]. 控制理论与应用, 2011, 28(1): 65-72. Liu Zhaohua, Zhang Yingjie, Zhang Jing, et al. A novel binary-state immune particle swarm optimization algorithm[J]. Control Theory & Applications, 2011, 28(1): 65-72.
[17]  Ling S H, Iu H H, Chan K Y, et al. Hybrid particle swarm optimization with wavelet mutation and its industrial applications[J]. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 2008, 38(3): 743-63.
[18]  Zhan Z H, Zhang J, Li Y, et al. Adaptive particle swarm optimization[J]. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 2009, 39(6): 1362-1380.

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