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

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Warianty tytułu
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.
Rocznik
Strony
43--57
Opis fizyczny
Bibliogr. 17 poz., rys.
Twórcy
autor
  • School of Electronic, Electrical and Computer Engineering College of Engineering and Physical Sciences. University of Birmingham, Birmingham, B15 2TT, U.K.
autor
  • Department of Control Systems Engineering, Faculty of Electrical and Control Engineering, Gdansk University of Technology, ul. Narutowicza 11/12, 80 – 233 Gdansk, Poland
Bibliografia
  • [1] MATLAB Genetic Algorithm Toolbox Manual.
  • [2] A. Bemporad and M. Morari. Robust model predictive control: A survey,. In Lecture Notes in Control and Information Sciences, volume 245, pages 207–226. Springer-Verlag, 1999.
  • [3] M.A. Brdys and T. Chang. Robust model predictive control under output constraints. In Proc. of the 15th IFAC World Congress, Barcelona, 2002.
  • [4] M.A. Brdys, K. Duxinkiewicz, T. Chang, M.Polycarpou, A. Wang, J. Uber, and M. Propato. Hierachical control of integrated quality and quantity in drinking water distribustion systems.In Proc. of the IFAC International Conference on Technology, Automation and Control of Wastewater Systems- TiASWiK’02, Gdansk – Sobieszewo, Poland, June 19–21, 2002.
  • [5] M.A. Brdys and B. Ulanicki. Operational Control of Water Systems: Structures, Algoritms and Applications. 1994.
  • [6] K. Deb. An efficient constraint handling method for genetic algorithms. Computer Methods in Applied Mechanics and Engineering, 186:311–338, 2000.
  • [7] D.E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley, 1989.
  • [8] M. Haestad, T.M. Walski, D.V. Chase, D.A. Savic, W. Grayman, S. Beckwith, and E. Koelle. Advanced Water Distribution Modeling and Management. Haestead Press, Waterbury, CT, 2003.
  • [9] J.H. Holland. Adaptation in Natural and Artificial Systems. MI: University of Michigan Press, Ann Arbor, 1975.
  • [10] J.M.Maciejowski. Predictive Control with Constraints. 2000.
  • [11] W. Kurek and M.A. Brdys. Genetic solver of optimisation task of mpc for optimising control of integrated quantity and quality in drinking water distribution systems. volume 11. IFAC– PapersOnLine, Elsevier, 2008.
  • [12] A. Ostfeld and E. Salomons. Optimal layout of early warning detection stations for water distribution systems security. Journal of Water Resources Planning and Management-Asce, 130:377–385, 2004.
  • [13] L.A. Rossman. EANET 2.0 Users manual. US Environmental Protection Agency, Cincinnati, 2000.
  • [14] D.A. Savic and G.A. Walters. Genetic algorithms for least-cost design of water distribution networks. Journal of Water Resources Planning and Management-Asce, 123:66–67, 1997.
  • [15] T.Chang and M. A. Brdys. Performance comparison of chlorine controllers based on input-output and state-space models. In Proc. of the 1st Annual Environmental & Water Resources Systems Analysis (EWRSA) Symposium, A.S.C.E. Environmental & Water Resources Institute (EWRI) Annual Conference, Roanoke, Virginia, May 19-22, 2002.
  • [16] B.A. Tolson, H.R. Maier, A.R. Simpson, and B.J. Lence. Genetic algorithms for reliability-based optimization of water distribution systems. Journal of Water Resources Planning and Management-Asce, 130:63–72, 2004.
  • [17] Z.Y. Wu and A.R. Simpson. Competent geneticevolutionary optimization of water distribution systems. Journal of Computing in Civil Engineering,15:89–101, 2001.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fd62d3e7-27aa-41d7-b3c2-2cde27c9bf2f
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