Robust optimal control for robotic manipulator

Abstract

Based on the Lagrange equation,the multi-joint robotic manipulator dynamical model is transformed into a linear state equation.And then,corresponding to the linear state equation,by solving a Linear Quadratic Regulator(LQR) problem,the robust optimal control law is obtained,which guarantee that the joint variables converge into the given point asymptotically in global sense.Finally,an example of two-joint robot is illustrated.Simulation results show that the proposed control law is very effective and indeed has robust performance.