变电站巡检机器人数据驱动无模型自适应控制

针对变电站巡检机器人动力学建模及参数辨识复杂等问题,文中提出了一种基于双闭环的巡检机器人数据驱动无模型自适应控制方法。首先,为了便于理解和仿真需要,对变电站巡检机器人的模型进行了简单的介绍。其次,根据机器人的位姿跟踪误差进行外环的设计,为内环提供虚拟参考输入。然后,根据无模型自适应控制方法进行内环控制器的设计,对机器人的虚拟参考速度进行跟踪。值得注意的是,文中所提方法只用到了输入输出数据,没有用到任何模型信息,因此是完全无模型的。最后,通过MATLAB进行仿真,验证了所提方法的有效性。

Data driven model free adaptive control for substation inspection robot

Considering the problems of dynamic modeling and parameter identification for the substation inspection robot, this paper proposes a data driven model free adaptive control method for the inspection robot based on double closed loop. Firstly, in order to facilitate understanding and simulation needs, the model of the substation inspection robot is briefly introduced. Secondly, the outer loop is designed to provide a virtual reference input for the inner loop according to the position error of the robot. Then, according to the model-free adaptive control method, the inner loop controller is designed to track the virtual reference speed of the robot. Note that, the method proposed in this paper only uses input and output data, no model information is used, so it is completely model free. Finally, the effectiveness of the proposed method is verified by simulation based on MATLAB.