Adaptive quantized control for uncertain nonlinear systems with unknown control directions
Jing Wu
School of Mathematics Science, Liaocheng University, Liaocheng, China
Search for more papers by this authorCorresponding Author
Wei Sun
School of Mathematics Science, Liaocheng University, Liaocheng, China
Correspondence Wei Sun, School of Mathematics Science, Liaocheng University, Liaocheng 252000, China.
Email: [email protected]
Search for more papers by this authorShun-Feng Su
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
Search for more papers by this authorYuqiang Wu
Institute of Automation, Qufu Normal University, Qufu, China
Search for more papers by this authorJing Wu
School of Mathematics Science, Liaocheng University, Liaocheng, China
Search for more papers by this authorCorresponding Author
Wei Sun
School of Mathematics Science, Liaocheng University, Liaocheng, China
Correspondence Wei Sun, School of Mathematics Science, Liaocheng University, Liaocheng 252000, China.
Email: [email protected]
Search for more papers by this authorShun-Feng Su
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
Search for more papers by this authorYuqiang Wu
Institute of Automation, Qufu Normal University, Qufu, China
Search for more papers by this authorFunding information: Major Scientific and Technological Innovation Project in Shandong Province, 2019JZZY011111; National Natural Science Foundation of China, 62073187; 61773191; Support Plan for Outstanding Youth Innovation Team in Shandong Higher Education Institutions, 2019KJI010; the Natural Science Foundation of Shandong Province for Key Projects, ZR2020KA010
Abstract
This study reports adaptive quantized control for a class of uncertain strict-feedback nonlinear systems with unknown control directions. Combining backstepping technique and Lyapunov stability theory, a systematic analysis method is designed. Based on the disintegration of the hysteresis quantizer, a Nussbaum-based scheme can be developed to get over the obstacle of the quantized input signal and unknown control directions. Moreover, the number of adaptive laws is small, thereby reducing the computational burden. Then we testify the boundedness of all signals in the closed-loop system. Besides, the tracking error can converge to an arbitrarily small domain of origin. Finally, a simulation example is provided to verify the feasibility of the control scheme.
CONFLICT OF INTEREST
No conflict of interest exists in the submission of this manuscript, and manuscript is approved by all authors for publication.
Open Research
DATA AVAILABILITY STATEMENT
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.
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Citing Literature
Special Issue:Emerging Approaches for Nonlinear Parameter Varying (NLPV) Systems
25 November 2021
Pages 8658-8671
