基于多变量特征模型的机械手自适应控制

机械手系统动力学模型所设计出来的控制器一般具有比较复杂的形式。为了解决机械手系统控制器复杂性问题,推导出机械手系统的线性多变量时变二阶离散差分方程,得到了其方程系数所满足的特征关系,并由分析可知当采样时间间隔足够小时,该方程系数具有慢时变特性。基于建立的差分方程及其系数的特征关系,给出了带有遗忘因子的最小二乘辨识方法和多变量黄金分割控制律相结合的且形式简单的自适应控制算法。利用系数的特征关系,能使需要辨识的参数个数减少。此算法具有只需要关节的位置信息而不需要速度信息的优点。数学仿真结果表明该方法对机械手控制的有效性和鲁棒性。

Manipulator Adaptive Control Based on Multi-Variable Characteristic Model

The designed controller based on the dynamics of robot manipulators is usually complex in form. To reduce tie complexity of the manipulator controller, a linear multivariable time-varying difference equation for robot manipulators was built up, and some valuable characteristic relations of the equation coefficients were found. After analyzing the equation, it could be seen that the coefficients of the equation change slowly with time if the sample time is small enough. Based on the difference equation and relations of its coefficients, an adaptive algorithm with simple form for the control of manipulators was presented, which combines the multi-variable Golden-Section adaptive controller with the Recursive Forgetting Factor method. With the coefficients' characteristic relations, the number of coefficients to be identified could be reduced greatly. Another advantage is that this algorithm merely needs the information of joint positions. The result of simulation showed that the developed method is effective and robust in manipulator control.