基于改进遗传算法辨识空间机器人动力学参数

为了减小空间机器人动力学参数的误差,提高轨迹规划精度,根据空间机器人的角动量守恒方程,利用名义动力学参数估计角动量与真实角动量的差异,建立动力学参数辨识的误差模型,给出遗传算法的适应度函数.针对常规遗传算法容易出现"早熟"现象,采用小区间生成法、大变异策略和精英保留策略对其进行了改进.以六关节空间机器人为例进行的仿真结果表明,在参数复杂的情况下,采用改进后的遗传算法,计算效率和辨识精度均得到了提高。

Identifying Dynamic parameters of a space robot based on improved genetic algorithm

To decrease the dynamic parameter errors of a space robot and improve accuracy of path planning,according to the angular momentum conservation equation,and based on the difference between the angular momentums estimated by nominal dynamic parameters and the real ones,an error model is built for the dynamic parameter identification,then the fitness function used for Genetic Algorithm(GA) is also presented.For "early maturity"phenomenon easily occurred in the conventional GA,an improved GA is presented based on small bound,big mutation and elite reservation tactics.At last,as an example of a six-joint space robot,a simulation is carried out.The results show that the improved GA increases calculative efficiency and identification accuracy in spite of complicated parameters.