Structurally optimized neural fuzzy modelling for model predictive control

Hu, X., Gong, Y., Zhao, D. and Gu, W. (2021) Structurally optimized neural fuzzy modelling for model predictive control. IEEE Transactions on Industrial Informatics, (doi: 10.1109/TII.2021.3133893) (Early Online Publication)

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This paper investigates the local linear model tree (LOLIMOT), a typical neural fuzzy model, in the multiple-input-multiple-output model predictive control (MPC). In the conventional LOLIMOT, the structural parameters including centres and variances of its Gaussian kernels are set based on equally dividing the input data space. In this paper, after the structural parameters are initially obtained from the input space partition, they are optimized by the gradient descent search, from which the space partitions are further adjusted. This makes it better for the model structure to fit the input data statistics, leading to improved modelling performance with small model size. The MPC based on the proposed structurally optimized LOLIMOT is then implemented and verified with both numerical and diesel engine plants. Validation results show that the proposed MPC has significantly better controlling performance than the MPC based on the conventional LOLIMOT, making it an attractive solution in practice.

Item Type:Articles
Additional Information:This work was supported by the Engineering and Physical Sciences Research Council of the U.K., through the EPSRC Innovation Fellowship, under Grant EP/S001956/2.
Status:Early Online Publication
Glasgow Author(s) Enlighten ID:Zhao, Dr Dezong
Authors: Hu, X., Gong, Y., Zhao, D., and Gu, W.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
Journal Name:IEEE Transactions on Industrial Informatics
ISSN (Online):1941-0050
Published Online:09 December 2021
Copyright Holders:Copyright © 2021 IEEE
First Published:First published in IEEE Transactions on Industrial Informatics 2021
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
314774Toward Energy Efficient Autonomous Vehiciles via Cloud-Aided learningDezong ZhaoEngineering and Physical Sciences Research Council (EPSRC)EP/S001956/2ENG - Autonomous Systems & Connectivity