基于数据驱动的变电站巡检机器人自抗扰控制

Data-driven Based Active Disturbance Rejection Control for Substation Inspection Robot

针对在变电站巡检机器人自抗扰控制(active disturbance rejection control,ADRC)系统中,不准确的控制输入矩阵会对控制性能产生影响的问题,提出一种基于数据驱动方法补偿的自抗扰控制架构.首先,给出巡检机器人离散时间动力学模型.其次,通过扩张状态观测器观测未建模动态、参数误差、摩擦力等不确定性,并根据机器人动力学模型设计ADRC控制器.然后将ADRC系统和机器人系统看作一个整体,使用数据驱动无模型自适应控制(model-free adaptive control,MFAC)方法完成轨迹追踪控制.值得注意的是,所提方法将ADRC方法和MFAC方法有机结合,形成了两者优势互补的工作机制.最后,通过仿真,验证了所提控制设计相对于传统的ADRC和MFAC方法的有效性.

An inaccurate control input matrix affects the control performance in the active disturbance rejection control(ADRC)system of a substation inspection robot.In this study,an ADRC scheme for an inspection robot based on a data-driven method is proposed to address this problem.First,the discrete time dynamic model of the inspection robot is established.Second,an extended state observer is used to observe parameter errors,unmodeled dynamics,friction,and other uncertainties.A nonlinear ADRC controller is devised on the basis of the dynamic model of the inspection robot.Then,the data-driven model-free adaptive control(MFAC)method is utilized for trajectory tracking control by considering the ADRC system and the robot system as a whole.Results reveal that the proposed method effectively combines the ADRC and MFAC methods.It also achieves the working mechanism with complementary advantages of the two control methods.Lastly,the effectiveness of the proposed method against traditional ADRC and MFAC methods is verified via simulations.