Command Filter-Based Adaptive Optimal Control of Uncertain Nonlinear Systems With Quantized Input

The issue of optimal output feedback control of uncertain nonlinear systems with quantized input is considered in this work. The fuzzy logic system is employed to approximate unknown nonlinearities and optimal cost. By incorporating the observer technique into command filtered backstepping control framework, the feedforward quantized control signal is designed. Then, the optimal feedback control signal for the constructed affine system is derived via single network adaptive dynamic programming. Finally, an optimal output feedback quantized control scheme is proposed. With the aid of adaptive compensating technique, the requirement for prior knowledge of quantization parameter is eliminated. The boundedness of all the signals in the closed-loop system is proved, and the output of system can reach the reference trajectory. Comparative simulations are implemented to verify the effectiveness of the proposed control strategy.