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Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system.
Mu, Qianqian; Long, Fei; Li, Bin.
Affiliation
  • Mu Q; College of Big Data and Information Engineering, Guizhou University, Guiyang, 550025, Guizhou, China. xtqqian@163.com.
  • Long F; School of Mathematics and Big Data, Guizhou Education University, Guiyang, 550018, Guizhou, China. xtqqian@163.com.
  • Li B; School of Artificial Intelligence and Electrical Engineering, Guizhou Institute of Technology, Guiyang, 550003, Guizhou, China.
Sci Rep ; 13(1): 8132, 2023 May 19.
Article in En | MEDLINE | ID: mdl-37208477
This paper investigates the adaptive neural network prescribed performance control problem for a class of dual switching nonlinear systems with time-delay. By using the approximation of neural networks (NNs), an adaptive controller is designed to achieve tracking performance. Another research point of this paper is tracking performance constraints which can solve the performance degradation in practical systems. Therefore, an adaptive NNs output feedback tracking scheme is studied by combining the prescribed performance control (PPC) and backstepping method. With the designed controller and the switching rule, all signals of the closed-loop system are bounded, and the tracking performance satisfies the prescribed performance.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep Year: 2023 Document type: Article Affiliation country: China Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep Year: 2023 Document type: Article Affiliation country: China Country of publication: United kingdom