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Cooperative Optimal Controller and Its Application to Activated Sludge Process.

Hong-Gui Han, Lu Zhang, Lin-Lin Zhang

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    A new cooperative optimal controller (COC) addresses challenges in the activated sludge process (ASP) by coordinating performance indices across different time scales. This method enhances operational efficiency and control performance in wastewater treatment.

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    Area of Science:

    • Environmental Engineering
    • Control Systems Engineering
    • Wastewater Treatment Technology

    Background:

    • The activated sludge process (ASP) faces challenges in coordinating performance indices due to increasing complexity and scale.
    • Managing different time scales of performance metrics in ASP is a significant operational hurdle.

    Purpose of the Study:

    • To propose a cooperative optimal controller (COC) for improving the operational performance of the activated sludge process.
    • To develop a control strategy that effectively coordinates multiple time-scale performance indices.

    Main Methods:

    • A cooperative optimal scheme was developed, formulating different time-scale performance indices into a two-level structure.
    • A data-driven surrogate-assisted optimization (DDSAO) algorithm was employed to optimize cooperative objectives using a surrogate model.
    • An adaptive predictive control strategy was investigated to derive control laws for enhanced tracking performance.

    Main Results:

    • The proposed COC effectively coordinated multiple time-scale performance indices in the activated sludge process.
    • The controller achieved competitive optimal control performance when tested on the benchmark simulation model No. 1 (BSM1).

    Conclusions:

    • The developed cooperative optimal controller (COC) offers a viable solution for managing complex activated sludge processes.
    • This approach demonstrates the ability to balance and optimize performance across various time scales, leading to improved wastewater treatment operations.