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Specialized genetic operators in drinking water distribution systems control

100%

Cimiński A. , Duzinkiewicz K.

tom z. 169

35-42

Model-based predictive control (MPC) is an effective method for control of the large scale systems. The method relying on repeating applying the first element of the calculated control sequence to the system, based on the model of the system and available system output measurements. A time duration of control calculation is a crucial criterion for applying this method. In this paper effective algorithm of control the drinking water distribution system (DWDS) is presented. Algorithm is based on genetic algorithm (GA), specialized genetic operators (SPO) and simulator Epanet. To improve the GA convergence, specialized genetic operators based on system operator knowledge of practical system control are proposed. Effectiveness of proposed specialized genetic operators on the example DWDS of the Chojnice city is presented.

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

100%

Tran V. N. , Brdys M. A.

Journal of Artificial Intelligence and Soft Computing Research

2011

tom Vol. 1, No. 1

43--57

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.