Nonlinear adaptive switching control for a class of non-affine nonlinear systems

Miao Huang; XinWang; Zhenlei Wang

doi:10.1016/j.cjche.2016.04.048

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Nonlinear adaptive switching control for a class of non-affine nonlinear systems

Process Systems Engineering and Process Safety | Updated：2026-01-06

- Nonlinear adaptive switching control for a class of non-affine nonlinear systems
- Chinese Journal of Chemical Engineering Vol. 24, Issue 9, Pages: 1243-1251(2016)
- Affiliations：
  
  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes, East China University of Science and Technology,Shanghai,China,200237
  2. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology,Shanghai,China,200093
  3. Center of Electrical & Electronic Technology, Shanghai Jiao Tong University,Shanghai,China,200240
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2016.04.048
  CLC： 10.1016/j.cjche.2016.04.048
- Published：2016
- Accepted：
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Miao Huang, XinWang, Zhenlei Wang. Nonlinear adaptive switching control for a class of non-affine nonlinear systems[J]. , 2016, 24(9): 1243-1251.
DOI：

Miao Huang, XinWang, Zhenlei Wang. Nonlinear adaptive switching control for a class of non-affine nonlinear systems[J]. , 2016, 24(9): 1243-1251. DOI： 10.1016/j.cjche.2016.04.048.

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Abstract

An improved nonlinear adaptive switching control method is presented to relax the assumption on the higher order nonlinear terms of a class of discrete-time non-affine nonlinear systems. The proposed control strategy is composed of a linear adaptive controller

a neural network (NN) based nonlinear adaptive controller and a switching mechanism. An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller. A new performance criterion of the switching mechanism is designed to select the proper controller. Using this control scheme

all the signals in the system are proved to be bounded. Numerical examples verify the effectiveness of the proposed algorithm.

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