Linear quadratic gaussian control design with extended KALMAN filter

Abstract

Linear quadratic problems are fundamental problem of optimal control system. These are introduced in linear system by additive white Gaussian noise. This problem is overcome with help of linear quadratic Gaussian controller. Controller is combination of optimal estimator and Kalman Filter used to compensate the noises in system.The main prospective of paper to design a LQG with Extended Kalman Filter for position control of dc servo motor. The direct implementation of LQG with kalman filter is adapting to change system parameters. EKF allows values of parameter estimation with unknown state of system. ANN based technique are used to compare characteristic of the controller different parameters. To evaluate system characteristics with three techniques 1) ANN 2) LQG 3) Extended Kalman Filter.