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Adaptive output feedback tracking for a class of nonlinear systems with quantized input and output
Author(s) -
Yu Xiaowei,
Lin Yan
Publication year - 2021
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5608
Subject(s) - control theory (sociology) , nonlinear system , quantization (signal processing) , output feedback , observer (physics) , tracking error , residual , computer science , mathematics , algorithm , control (management) , artificial intelligence , physics , quantum mechanics
In this paper, an adaptive output feedback tracking for a class of uncertain nonlinear systems with input and output quantization is investigated. A new controller structure is introduced in which a modified output quantizer is proposed so that its first‐order derivative exists, and an observer is designed with quantized input and output as its input signals. Then, with dynamic surface control as a tool, an adaptive recursive design is developed which can avoid higher‐order derivatives of the quantized output signal. It is proved that, with the proposed scheme, coarser input and output quantization can be achieved and the tracking error can converge to a small residual set by appropriately choosing some design parameters.