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PID Based Nonlinear Processes Control Model Uncertainty Improvement by Using Gaussian Process Model

Chen, LLT, Chen, T and Chen, J (2016) PID Based Nonlinear Processes Control Model Uncertainty Improvement by Using Gaussian Process Model Journal of Process Control, 42. pp. 77-89.

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Abstract

Proportional-integral-derivative (PID) controller design based on the Gaussian process (GP) model is proposed in this study. The GP model, defined by its mean and covariance function, provides predictive variance in addition to the predicted mean. GP model highlights areas where prediction quality is poor, due to the lack of data, by indicating the higher variance around the predicted mean. The variance information is taken into account in the PID controller design and is used for the selection of data to improve the model at the successive stage. This results in a trade-off between safety and the performance due to the controller avoiding the region with large variance at the cost of not tracking the set point to ensure process safety. The proposed direct method evaluates the PID controller design by the gradient calculation. In order to reduce computation the characteristic of the instantaneous linearized GP model is extracted for a linearized framework of PID controller design. Two case studies on continuous and batch processes were carried out to illustrate the applicability of the proposed method.

Item Type: Article
Subjects : Chemical and Process Engineering
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
AuthorsEmailORCID
Chen, LLTUNSPECIFIEDUNSPECIFIED
Chen, TUNSPECIFIEDUNSPECIFIED
Chen, JUNSPECIFIEDUNSPECIFIED
Date : June 2016
Identification Number : 10.1016/j.jprocont.2016.03.006
Copyright Disclaimer : © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords : Approximation, Gaussian process, Model update, PID control
Depositing User : Symplectic Elements
Date Deposited : 11 Jul 2016 12:42
Last Modified : 11 Jul 2016 12:42
URI: http://epubs.surrey.ac.uk/id/eprint/811163

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