基于DCNLP的机器手臂最优化控制及拉格朗日因子研究

A STUDY ON MANIPULATOR ARM OPTIMAL CONTROL AND LAGRANGE MULTIPLIER USING DCNLP

为使机器手臂圆满地完成医疗搀扶等既定看护工作的同时能耗达到最低,针对机器手臂在医疗看护时的两个基本动作(拦截接住,对接捕获),描述并建立机器手臂的动力学方程,构建案例模型,并分别引入最优化控制技术,对最优控制问题进行离散并数字求解,得到系统的最优解;并基于上述工作基础,针对详述能耗J和各个限制方程微小异动之间关系的拉格朗日因子,深入探讨该两案例中的拉格朗日因子的不同表现。从案例结果分析,相对于传统方法求解能耗最优化问题,DCNLP法表现出了较好的鲁棒性,对初始值的估算要求较低,探讨的结果能对机器手臂如何更好地完成要求操作给出积极建议。

In order to have the manipulator arm consummately complete the established caregiving works of medical arm supporting and propping while minimising the energy consumption,aiming at two basic motions of manipulator arm＇s medical caregiving,the interception catch and the docking capture,we describe and establish the dynamics equation for manipulator arm,construct case model,and introduce optimal control technology respectively,we scatter the optimal control problem and make digital solution to obtain the optimal solution;Moreover,based on the above working basis,and aiming at the Lagrange multiplier which recounting the relationship between the energy consumption J and the tiny abnormal motion of each restriction equation,we thoroughly discuss the different performances of the Lagrange multipliers in two cases.Analyses derived from the cases results demonstrate that,DCNLP method performs well in robustness in contrast to the traditional method used for solving energy consumption optimisation,it has lower requirement on initial estimation.The discuss result can provide active suggestion for manipulator arm in terms of the way to better complete the required operation.