Adaptive decoupling switching control based on generalised predictive control

Author(s): Y. Wang ; T. Chai ; J. Fu ; Y. Zhang ; Y. Fu
DOI: 10.1049/iet-cta.2011.0053

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Author(s): Y. Wang ¹ ; T. Chai ¹ ; J. Fu ¹ ; Y. Zhang ¹ ; Y. Fu ¹
- Affiliations: 1: State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, People’s Republic of China
Source: Volume 6, Issue 12, 16 August 2012, p. 1828 – 1841
DOI: 10.1049/iet-cta.2011.0053 , Print ISSN 1751-8644, Online ISSN 1751-8652

This study introduces a multivariable adaptive decoupling control strategy using multiple models and neural networks for a class of discrete-time nonlinear dynamic systems. The adaptive decoupling switching control strategy based on generalised predictive control is composed of a linear adaptive decoupling controller, a neural-network-based nonlinear adaptive decoupling controller and a switching mechanism. First, the linear adaptive decoupling controller is designed to ensure the boundedness of the input and output signals of the closed-loop system. Second, the neural-network-based nonlinear adaptive decoupling controller is developed to improve the transient performance of the closed-loop system. Third, the stability and convergence of the closed-loop system are achieved simultaneously by using multiple-models-based switching mechanism. Simulation studies are provided for a numerical example and a forced-circulation evaporation process of an alumina production system so as to demonstrate the effectiveness of the proposed method.

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Adaptive decoupling switching control based on generalised predictive control

Adaptive decoupling switching control based on generalised predictive control

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