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

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  • Chen, Chen
  • Li, Jinghao

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.

Suggested Citation

  • Chen, Chen & Li, Jinghao, 2025. "A composite filter-based approach to adaptive prescribed-time output-feedback control of strict-feedback nonlinear systems with output and input quantization," Applied Mathematics and Computation, Elsevier, vol. 494(C).
    • Handle: RePEc:eee:apmaco:v:494:y:2025:i:c:s0096300325000062
    DOI: 10.1016/j.amc.2025.129279
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