Design and performance analysis of adaptive linear quadratic Gaussian controller

In this paper, the design process and performance analysis of Adaptive Linear Quadratic Gaussian (ALQG) control are presented. The controller is expected to control the speed of separately excited DC motor (SEDCM). Implement of this control law is performed trough the use of separation theorem, which involves the design of a Kalman estimator and a linear quadratic controller separately. A robust identification algorithm is used for the online estimation of a linear SISO model's parameters. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.