Title :
RBF-ARX Modeling and Predictive Control Strategy Applied to a Liquid Level System
Author :
Garba, Inoussa ; Hui, Peng ; Lin, Ren
Author_Institution :
Central South Univ., Changsha
Abstract :
The main objective of this paper is to show in the first place that the RBF-ARX modeling technique can be used to model a dynamic nonlinear SISO liquid level system with higher precision and then to demonstrate that when the model obtained is taken as predictor of a model predictive controller (MPC) one may obtain an enhanced control performance. The RBF-ARX model is in fact a locally expanded Taylor ARX model with Gaussian radial basis function (RBF) network-style coefficients depending of the working point; it can be estimated offline to avoid any online uncertainty. It is built to globally describe the behavior of nonlinear dynamic system and exhibit an easy and advantageous means of obtaining a local linearization of any working point. The RBF-ARX model based MPC (RBF-ARX-MPC) is a predictive control strategy based on RBF-ARX model. It doesn´t require online but offline parameters optimization in which the nonlinear parameters estimation depends on the Levenberg-Marquardt Method (LMM) and the linear one on the least-square method using singular value decomposition (SVD).
Keywords :
Gaussian processes; control engineering computing; least mean squares methods; level control; nonlinear dynamical systems; predictive control; radial basis function networks; singular value decomposition; Gaussian radial basis function network; Levenberg-Marquardt method; RBF-ARX modeling; least-square method; model predictive controller; nonlinear SISO liquid level system; nonlinear dynamic system; singular value decomposition; Chemical industry; Control systems; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Optimization methods; Parameter estimation; Power system modeling; Predictive control; Predictive models; Liquid-level system; MPC; RBF-ARX model; modeling; nonlinear system; water tank;
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
DOI :
10.1109/CHICC.2006.4347149