Joint robust position control using linear Kalman filters

Abstract

A new control strategy for robotic manipulators is discussed. Some simulation results obtained in the Matlab/Simulink environment are presented. The position control system design is based on a local PD control technique with a feedforward compensation term. The PD controller is designed considering a first order linear reference model for each joint. The controller gains are tuned on average values of the inertial moments, evaluated in the range of the allowable configurations of the manipulator links, and on nominal viscous friction coefficients. The robustness of the proposed control system is guaranteed by the recursive algorithm, based on the discrete linear Kalman filter (LKF) theory, which has been developed to online estimate the nonlinear time varying equivalent disturbance. The LKF also gives the estimates of position and speed that are used as feedback signals for the joint control system.