Adaptive pseudo linear RBF model for process control

Authors:
Ding-Wen Yu;Ding-Li Yu
Affiliations:
Department of Automation, Northeast University at Qinhuangdao, China;Control Systems Research Group, School of Engineering, Liverpool John Moores University, Liverpool, UK
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

Citing 2
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Abstract

A pseudo-linear radial basis function (PLRBF) network is developed in this paper. This network is used to model a real process and its weights are on-line updated using a recursive orthogonal least squares (ROLS) algorithm. The developed adaptive model is then used in model predictive control strategy, which is applied to a pilot multivariable chemical reactor. The first stage of the project, simulation study, has been investigated and is presented. The effectiveness of the adaptive control in improving the closed-loop performance has been demonstrated for process time-varying dynamics and model-process mismatch.