Parametric Neural Network-Based Model Free Adaptive Tracking Control Method and Its Application to AFS/DYC System | Zendy

Zhijun Fu | Zendy; Yan Lü | Zendy; Fang Zhou | Zendy; Yaohua Guo | Zendy; Pengyan Guo | Zendy; Heyang Feng | Zendy

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Parametric Neural Network-Based Model Free Adaptive Tracking Control Method and Its Application to AFS/DYC System

Author(s) -

Zhijun Fu,

Yan Lü,

Fang Zhou,

Yaohua Guo,

Pengyan Guo,

Heyang Feng

Publication year - 2022

Publication title -

computational intelligence and neuroscience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.605

H-Index - 52

eISSN - 1687-5273

pISSN - 1687-5265

DOI - 10.1155/2022/4579263

Subject(s) - control theory (sociology) , computer science , identifier , controller (irrigation) , convergence (economics) , nonlinear system , artificial neural network , adaptive control , parametric statistics , lyapunov function , identification (biology) , trajectory , system identification , term (time) , tracking error , artificial intelligence , control (management) , mathematics , measure (data warehouse) , data mining , statistics , physics , botany , quantum mechanics , astronomy , agronomy , economics , biology , programming language , economic growth

This paper deals with adaptive nonlinear identification and trajectory tracking problem for model free nonlinear systems via parametric neural network (PNN). Firstly, a more effective PNN identifier is developed to obtain the unknown system dynamics, where a parameter error driven updating law is synthesized to ensure good identification performance in terms of accuracy and rapidity. Then, an adaptive tracking controller consisting of a feedback control term to compensate the identified nonlinearity and a sliding model control term to deal with the modeling error is established. The Lyapunov approach is synthesized to ensure the convergence characteristics of the overall closed-loop system composed of the PNN identifier and the adaptive tracking controller. Simulation results for an AFS/DYC system are presented to confirm the validity of the proposed approach.

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