A novel learning control method of macro-micro robot

A novel control scheme on learning frame is proposed for control of uncertain robot manipulator performing periodic tasks. In the paper, the uncertainties in the robot system may follow non-Gaussian distribution or Gaussian distribution, but the premise condition is that they are bounded. The nonlinear relation formulation between controller gain and tracking trajectory error of robot in each batch has been given. The optimal process of controller gain has been presented by using the proposed ILC frame. In the end, the convergence condition is analyzed and the experimental result is given. It is shown that all the error signals in the learning control system are bounded and the robot motion trajectory converges to the desired one asymptotically. Experimental results demonstrate the feasibility and effectiveness of the proposed control method for repetive robot motion.