Adaptive tracking control for a class of nonlinear systems with input dead-zone and actuator failure
Ming Lei
School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing, 210094 Jiangsu, P. R. China
Search for more papers by this authorCorresponding Author
Weimin Chen
School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing, 210094 Jiangsu, P. R. China
Correspondence
Weimin Chen, School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, P. R. China.
Email: [email protected]
Communicated by: R. P. Agarwal
Search for more papers by this authorLanning Wang
School of Science, Nanjing University of Posts and Telecommunications, Nanjing, 210023 Jiangsu, P. R. China
Search for more papers by this authorMing Lei
School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing, 210094 Jiangsu, P. R. China
Search for more papers by this authorCorresponding Author
Weimin Chen
School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing, 210094 Jiangsu, P. R. China
Correspondence
Weimin Chen, School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, P. R. China.
Email: [email protected]
Communicated by: R. P. Agarwal
Search for more papers by this authorLanning Wang
School of Science, Nanjing University of Posts and Telecommunications, Nanjing, 210023 Jiangsu, P. R. China
Search for more papers by this authorFunding information: This work is supported by National Nature Science Foundation of China under Grant 61573007.
Abstract
In this paper, the adaptive tracking problem for a class of strictly feedback nonlinear time-delay systems with output constraints, actuator failures, and input dead zones is studied. First, in the design of controller, the absolute value function and integral term are introduced into the candidate functions to deal with nonlinear factors and distributed time-varying delays in the system. In addition, an adaptive neural network controller is designed to ensure the stability of the controlled system, and the system tracking error can converge to the origin without violating the constraints. Finally, simulation results verify the feasibility of the proposed control strategy.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to in influence the work reported in this paper.
AUTHOR CONTRIBUTIONS
Ming Lei contributed to the writing-draft preparation original, data curation, software, and validation. Weimin Chen contributed to the conceptualization, methodology, writing-reviewing, and editing. Lanning Wang contributed to the conceptualization, writing-reviewing, and editing.
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