This paper deals with a design problem of an observer-based robust preview control system for uncertain discrete-time systems. In this approach, we adopt 2-stage design scheme and we derive an observer-based robust controller with integral and preview actions such that a disturbance attenuation level is satisfactorily small for allowable uncertainties.

In this paper, we propose an integral-type T-S fuzzy control scheme to deal with the regulation problem of buck converters without current sensors. This current sensorless control of converters provides the output voltage to achieve zero steady-state error and is with high robust performance. The stability of the overall closed-loop system is rigorously analyzed by using Lyapunov's method. Based on an appropriate assumption, the separation principle can still succeed in the control problems. Hence, the controller and observer gains can be separately obtained by solving LMIs via Matlab's toolbox. The observer-based controller is realized with Simulink and digital signal processors (DSPs). The simulation and experimental results verify the feasibility of the proposed schemes and show the satisfactory performance for the power converters.

In this paper, we present an output feedback controller using a fuzzy controller and observer for nonlinear systems with unknown time-delay. Recently, Cao et al. proposed a stabilization method for the nonlinear time-delay systems using a fuzzy controller when the time-delay is known. In general, however, it is impossible to know or measure this time-varying delay. The proposed method requires only the upper bound of the derivative of the time-delay. We represent the nonlinear system with the unknown time-delay by Takagi-Sugeno (T-S) fuzzy model and design the fuzzy controller and observer for the systems using the parallel distributed compensation (PDC) scheme. In addition, we derive the sufficient condition for the asymptotic stability of the equilibrium point by applying Lyapunov-Krasovskii theorem to the closed-loop system and solve the condition in the formulation of LMI. Finally, computer simulations are included to demonstrate the effectiveness of the suggested method.