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针对传统感应电机参数辨识方法中存在的可辨识参数少、辨识精度低等缺陷,提出了一种禁忌混沌萤火虫算法对感应电机参数进行辨识。该方法能够同时辨识定子电阻、定子电感、转子时间常数和漏感,且对辨识参数没有严苛的先验要求。为了提高参数的辨识精度,改进了算法吸引度公式并融入混沌理论和禁忌搜索的思想以克服萤火虫算法收敛精度低、易于陷入局部最优的不足。仿真表明,相较于其他3种算法,该算法具有较强的稳定性和较好的收敛精度,并能在不同转速和负载的情况下,以较短时间将辨识参数收敛到真实值附近,具有实用性。
Aiming at the shortcoming of the traditional induction motor parameter identification methods, such as less identifiable parameters and low recognition accuracy, a taboo chaos firefly algorithm is proposed to identify the parameters of the induction motor. This method can identify stator resistance, stator inductance, rotor time constant and leakage inductance at the same time, and there are no strict a priori requirements on the identification parameters. In order to improve the identification accuracy of parameters, the algorithm’s attraction degree formula is improved and the idea of chaos theory and tabu search is incorporated to overcome the disadvantage of the firefly algorithm’s low convergence accuracy and easy falling into local optimum. The simulation results show that compared with the other three algorithms, the proposed algorithm has better stability and better convergence precision, and can converge the identification parameters near the real value in a shorter time under different speeds and loads. Practical.