EXTENDED LQG SELF-TUNING CONTROLLER IN A MIXED BACKGROUND

Abstract

We consider the problem of constructing a LQG-based adaptive controller so that the control system can track a deterministic command signal and simultaneously regulate stochastic disturbances. A new measure for mixed signal in the feedback loop is first introduced. Then a generalized cost function is formulated and the optimal 'extended LQG controller' can be constructed by solving a diophantine equation. Based on the extended LQG design, a self-tuning controller can be constructed. System tracking performance under ergodic process noise is analysed in detail and better results are obtained. Finally, the optimal tracking performance is attained if the parameter estimates converge to their true values.