中国科学:信息科学(英文版)2024,Vol.67Issue(7) :220-235.DOI:10.1007/s11432-023-3949-3

Adaptive neural network control of a 2-DOF helicopter system considering input constraints and global prescribed performance

Zhijia ZHAO Jiale WU Zhijie LIU We HE C.L.Philip CHEN
中国科学:信息科学(英文版)2024,Vol.67Issue(7) :220-235.DOI:10.1007/s11432-023-3949-3

Adaptive neural network control of a 2-DOF helicopter system considering input constraints and global prescribed performance

Zhijia ZHAO 1Jiale WU 1Zhijie LIU 2We HE 2C.L.Philip CHEN3
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作者信息

  • 1. School of Mechanical and Electrical Engineering,Guangzhou University,Guangzhou 510006,China
  • 2. School of Intelligence Science and Technology and Key Laboratory of Intelligent Bionic Unmanned Systems of Ministry of Education,University of Science and Technology Beijing,Beijing 100083,China
  • 3. School of Computer Science and Engineering,South China University of Technology,Guangzhou 510641,China;Pazhou Lab,Guangzhou 510335,China
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Abstract

In this study,an adaptive neural network(NN)control is proposed for nonlinear two-degree-of-freedom(2-DOF)helicopter systems considering the input constraints and global prescribed performance.First,radial basis function NN(RBFNN)is employed to estimate the unknown dynamics of the helicopter system.Second,a smooth nonaffine function is exploited to approximate and address nonlinear constraint functions.Subsequently,a new prescribed function is proposed,and an original constrained error is trans-formed into an equivalent unconstrained error using the error transformation and barrier function transfor-mation methods.The analysis of the established Lyapunov function proves that the controlled system is globally uniformly bounded.Finally,the simulation and experimental results on a constructed Quanser's test platform verify the rationality and feasibility of the proposed control.

Key words

adaptive NN control/2-DOF helicopter/global prescribed performance/input constraints

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基金项目

National Key Research and Development Program of China(2023YFB4706400)

National Natural Science Foundation of China(62273112)

National Natural Science Foundation of China(62225304)

National Natural Science Foundation of China(92267203)

Science and Technology Major Project of Guangzhou(202007030006)

Science and Technology Planning Project of Guangzhou(202201020185)

Science and Technology Planning Project of Guangzhou(2023A03J0120)

Program for Guangdong Introducing Innovative and Entrepreneurial Teams(2019ZT08X214)

Guangzhou University Research Project(RC2023037)

出版年

2024
中国科学:信息科学(英文版)
中国科学院

中国科学:信息科学(英文版)

CSTPCDEI
影响因子:0.715
ISSN:1674-733X
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