K-Filter Observer Based Optimal Robust Guarantee Cost Control for Uncertain Nonlinear Servo System with Immeasurable States

In this paper, a K-filter observer based optimal robust guarantee cost controller is proposed for uncertain nonlinear servo system with immeasurable states to achieve the precision load tracking. By using a K-filter observer to estimate both the system states and the nonlinearities, an adaptive dynamic surface control is designed to make the system output track a given reference command. However, since the parameter uncertainties may influence the system tracking performance, an optimal robust guarantee cost control is developed to combine with the adaptive dynamic surface control to stabilize the uncertain system and guarantee the system cost function less than or equal to a given upper bound. The Lyapunov theory proves the stability of the closed-loop control system. Simulation results based on a servo system are conducted to illustrate the efficiency of the proposed control scheme.