Quantized Decentralized Adaptive Neural Network PI Tracking Control for Uncertain Interconnected Nonlinear Systems with Dynamic Uncertainties

Haibin Sun, Guangdeng Zong, Choon Ki Ahn

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

Abstract

In this paper, a decentralized adaptive neural network proportional-integral (PI) tracking control scheme is proposed for interconnected nonlinear systems with input quantization and dynamic uncertainties. This algorithm is underpinned by the use of the dynamic signal, graph theory, and function recombination to deal with the difficulties existing in the nontriangular form, unmodeled dynamics, and unknown interconnected terms. Recalling the backstepping method and neural network approximation technology, a new PI tracking controller characterized by simple structure and easy implementation is developed which ensures that all the closed-loop signals are uniformly ultimately bounded. The effectiveness of the obtained controller is exemplified via a numerical example and an application to an inverted pendulum.

Original languageEnglish
Article number8736513
Pages (from-to)3111-3124
Number of pages14
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume51
Issue number5
DOIs
Publication statusPublished - 2021 May

Bibliographical note

Funding Information:
Manuscript received December 15, 2018; revised March 28, 2019; accepted May 10, 2019. Date of publication June 13, 2019; date of current version April 15, 2021. This work was supported in part by the National Natural Science Foundation of China under Grant 61773236, Grant 61773235, Grant 61873331, Grant 61803225, and Grant 61703233, in part by the Taishan Scholar Project of Shandong Province under Grant TSQN20161033 and Grant ts201712040, in part by the Post-Doctoral Science Foundation of China under Grant 2017M612236, and in part by the National Research Foundation of Korea through the Ministry of Science, ICT and Future Planning under Grant NRF-2017R1A1A1A05001325. This paper was recommended by Associate Editor Z.-G. Wu. (Corresponding author: Guangdeng Zong.) H. Sun and G. Zong are with the School of Engineering, Qufu Normal University, Rizhao 276826, China (e-mail: fengyun198212@163.com).

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Decentralized control
  • input quantization
  • interconnected system
  • neural network-based control
  • nontriangular form
  • proportional-integral (PI) tracking controller

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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