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Title: | MIMO model predictive control with local linear models |
Author: | Novák, Jakub; Chalupa, Petr; Bobál, Vladimír |
Document type: | Conference paper (English) |
Source document: | Recent Researches in Automatic Control - 13th WSEAS International Conference on Automatic Control, Modelling and Simulation, ACMOS'11. 2011, p. 189-194 |
ISBN: | 978-1-61804-004-6 |
Abstract: | The performance of a Model Predictive Control (MPC) algorithm depends on the quality of the derived model. Using a divide-and-conquer strategy process operations were partitioned into several operating regions and within each region, a local linear model was developed to model the process. This set of locally linearized models was simply and effectively combined into a global description of a multivariable nonlinear plant. To save on computational load, a linear model was obtained by interpolating these linear models at each sample point and then this linearized model was used in a Generalized Predictive Control (GPC) framework to calculate the future behavior of the process. Thus, time-consuming nonlinear quadratic optimization calculations, which are normally necessary in nonlinear predictive control, can be avoided. Modeling and controller design procedure was demonstrated using a simulated pH neutralization process with two inputs and two outputs. |
Full text: | http://www.wseas.us/e-library/conferences/2011/Lanzarote/ACMOS/ACMOS-35.pdf |
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