A composite filter-based approach to adaptive prescribed-time output-feedback control of strict-feedback nonlinear systems with output and input quantization

Abstract

This paper investigates the adaptive prescribed-time control problems of strict-feedback nonlinear systems with output quantization, input quantization and unknown control coefficients. Firstly, a quantized K-filter is constructed to estimate the system states. Then, a set of command filters are introduced to smooth the discontinuous stabilizing functions and reduce the computational burden. Moreover, a class of scaling functions are designed to achieve the desired prescribed-time tracking performance. Based on the quantized K-filter, a set of command filters and a class of scaling functions, a set of new error variables are established to facilitate the design of the quantized composite filter-based adaptive prescribed-time control method. It is proved that the tracking error converges to an adjustable compact set within a prescribed time. Finally, two examples are provided to illustrate the effectiveness of the proposed method.