Optimizing control by robustly feasible model predictive control and application to drinkingwater distribution systems

• Autorzy: Tran V. N. , Brdys M. A.
• Języki publikacji: EN

Abstrakty

EN

The paper considers optimizing Model Predictive Control (MPC) for nonlinear plants with output constraints under uncertainties. Although the MPC technology can handle the constraints in the model by solving constraint model based optimization task, satisfying the plant output constraints under the model uncertainty still remains a challenge. The paper proposes Robustly Feasible MPC (RFMPC), which achieves feasibility of the outputs in the controlled plant. The RFMPC which is applied to control quantity in Drinking Water Distribution Systems (DWDS) is illustrated by application to the DWDS example. In the simulation exercise, Genetic Algorithm is selected as the optimization solver and the reduced search space methodology is applied in the implementation under MATLABEPANET environment.

Słowa kluczowe

EN

optimizing; model predictive control; MPC; Robustly Feasible MPC; RFMPC; Drinking; Water Distribution Systems; DWDS; genetic algorithm

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2011
• Tom: Vol. 1, No. 1
• Strony: 43--57
• Opis fizyczny: Bibliogr. 17 poz., rys.

Twórcy

autor

Tran V. N.

• School of Electronic, Electrical and Computer Engineering College of Engineering and Physical Sciences. University of Birmingham, Birmingham, B15 2TT, U.K.

autor

Brdys M. A.

• Department of Control Systems Engineering, Faculty of Electrical and Control Engineering, Gdansk University of Technology, ul. Narutowicza 11/12, 80 – 233 Gdansk, Poland

Bibliografia

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