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Xianjun Du1, Yu Peng2

  • 1College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China E-mail: xdu@lut.edu.cn; Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou 730050, China; National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou 730050, China.

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Summary
This summary is machine-generated.

A new heterogeneous multi-group competitive algorithm (HMCA) improves parameter estimation for the Activated Sludge Model 1 (ASM1). This wastewater treatment model enhancement offers faster convergence and higher accuracy in simulations.

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Area of Science:

  • Environmental Engineering
  • Wastewater Treatment Technologies
  • Biochemical Process Modeling

Background:

  • Activated Sludge Model 1 (ASM1) is crucial for wastewater treatment simulations but suffers from parameter uncertainty and slow, inaccurate estimation algorithms.
  • Accurate ASM1 parameter estimation is vital for ensuring effluent quality meets discharge standards in industrial practice.

Purpose of the Study:

  • To develop a novel, efficient, and practical algorithm for estimating ASM1 parameters.
  • To address the limitations of existing algorithms, including slow convergence and low accuracy.

Main Methods:

  • Introduction of the heterogeneous multi-group competitive algorithm (HMCA), integrating a Legendre function network and dynamic partitioning strategy.
  • Validation of HMCA performance against eight state-of-the-art algorithms using test functions.
  • Application of HMCA to Benchmark Simulation Model no. 1 (BSM1) with operational data.

Main Results:

  • HMCA demonstrated superior convergence speed and accuracy compared to existing methods.
  • The algorithm effectively overcame issues of slow convergence and low accuracy in ASM1 parameter estimation.
  • Validation confirmed HMCA's applicability and enhanced performance in real-world wastewater treatment scenarios.

Conclusions:

  • The heterogeneous multi-group competitive algorithm (HMCA) offers a significant advancement for ASM1 parameter estimation.
  • HMCA provides a more efficient and practical solution for wastewater treatment process modeling and simulation.
  • This improved parameter estimation enhances the reliability of wastewater treatment simulations for regulatory compliance.