Parameter identification of mine-used robot driving system
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摘要: 针对基于最小二乘法的参数辨识精度不高的问题,提出了一种基于鲸鱼优化算法的矿用机器人驱动系统参数辨识方法。通过建立矿用机器人驱动系统模型确定待辨识参数,将待辨识参数看作鲸鱼群个体位置,通过适应度函数来衡量每个鲸鱼群个体位置的优劣,利用鲸鱼觅食策略不断更新鲸鱼群个体位置,直至获得最佳鲸鱼群个体位置,即可获得最佳辨识参数。仿真和实验结果表明,与基于最小二乘法的参数辨识方法相比,该方法具有更高的辨识精度。Abstract: In view of problem of low precision of parameter identification based on least square method, a parameter identification method of mine-used robot driving system based on whale optimization algorithm was proposed. Driving system model of mine-used robot is established to determine parameters to be identified which are considered as individual position of whale colony. Fitness function is used to measure the individual position of whale colony. The optimal identification parameters can be obtained by continuously updating the individual position of whale colony with whale foraging strategy until the optimal individual position of whale colony is obtained. The simulation and experimental results show that the method has higher identification accuracy than the parameter identification method based on least square method.
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