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Neural Computing and Applications

Observer-based adaptive finite-time prescribed performance NN control for nonstrict-feedback nonlinear systems

  • 22-03-2022
  • Original Article
Published in:
Authors
Dongbing Tong
Xiang Liu
Qiaoyu Chen
Wuneng Zhou
Kaili Liao
Published in
Neural Computing and Applications | Issue 15/2022

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Abstract

The article introduces an innovative control strategy for nonstrict-feedback nonlinear systems, incorporating neural networks to handle uncertainties and adaptive backstepping to manage complexity. The method ensures system stability and precise tracking performance within finite time, overcoming challenges such as algebraic loop problems and full-state constraints. By employing a dynamic surface control approach and a finite-time performance function, the proposed controller guarantees that the system remains within predefined bounds, offering a robust solution for practical engineering applications.
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Title
Observer-based adaptive finite-time prescribed performance NN control for nonstrict-feedback nonlinear systems
Authors
Dongbing Tong
Xiang Liu
Qiaoyu Chen
Wuneng Zhou
Kaili Liao
Publication date
22-03-2022
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 15/2022
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-022-07123-6
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