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An optimizing control of a wastewater treatment plant (WWTP), allowing for cost savings over long time period and fulfilling effluent discharge limits at the same time, requires application of advanced control techniques. Model Predictive Control (MPC) is a very suitable control technology for a synthesis of such a truly multivariable controller that can handle constraints and accommodate model-based knowledge combined with hard measurements. As it is impossible to efficiently control the plant by one universal control strategy under all possible influent conditions, it is proposed in the paper to on-line adapt the nonlinear MPC control strategy in order to best adapt the control actions to actual and predicted WWTP conditions. Adjusting the MPC control strategy is carried out by suitable manipulating the components of performance index and constraints. This process is supervised by Mamdani reasoning system. The supervised MPC controller performance was tested by simulations within large range of plant operating conditions and then compared with classic MPC without such mechanism. The simulation model of the benchmark WWTP utilizes ASM2d model.
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- Kategoria:
- Aktywność konferencyjna
- Typ:
- materiały konferencyjne indeksowane w Web of Science
- Tytuł wydania:
- 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR) strony 613 - 618
- Język:
- polski
- Rok wydania:
- 2016
- Opis bibliograficzny:
- Grochowski M., Rutkowski T..: Supervised model predictive control of wastewater treatment plant, W: 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR), 2016, IEEE,.
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1109/mmar.2016.7575206
- Weryfikacja:
- Politechnika Gdańska
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