Abstract：An ant colony vector moving algorithm is proposed to identify the load torque and moment of inertia for load-running permanent magnet synchronous motor (PMSM) servo system while run-time loading, in order to adjust the PI parameters and compensate the torque. Vector moving is decomposed into horizontal and vertical directions, one for moment of inertia, the other for load torque, and every ant position means one possible solution. With the sampled sequences d-axis current and speed data, based on the minimum variance principle, the pheromone expression model is established, making the closer distance between the ant position and actual load and inertia, the more pheromone. The expecting distribution for ant colony is calculated after the total pheromone statistics. The ant colony is inspired to move towards the optimal direction with the convergence point for the identified results. The normalized distribution for ant colony is selected to improve convergence performance when the dynamic ant colony distribution is converted to the normalized range. Simulations and experiments show the two parameters can be identified at the same time with the small error; and the error can become smaller if ant colony scale becomes bigger, and the dynamic performance is excellent after adjusting PI according to the identified values.
王少威, 万山明, 周理兵, 黄声华. 利用蚁群算法辨识PMSM伺服系统负载转矩和转动惯量[J]. 电工技术学报, 2011, 26(6): 18-25.
Wang Shaowei, Wan Shanming, Zhou Libing, Huang Shenghua. Identification of PMSM Servo System’s Load Torque and Moment of Inertia by Ant Colony Algorithm. Transactions of China Electrotechnical Society, 2011, 26(6): 18-25.
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