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Parameter estimation of activated sludge process based on an improved cuckoo search algorithm.

Xianjun Du1, Junlu Wang2, Veeriah Jegatheesan3

  • 1College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China; School of Engineering, RMIT University, Melbourne 3000, Australia; 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.

Accurate kinetic parameters are crucial for activated sludge models in wastewater treatment. An improved cuckoo search algorithm enhances parameter estimation for the Activated Sludge Model No. 1 (ASM1), improving wastewater treatment process predictions.

Keywords:
ASM1Activated sludge processCuckoo search algorithmParameter estimationWastewater treatment

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Area of Science:

  • Environmental Engineering
  • Computational Fluid Dynamics
  • Biochemical Engineering

Background:

  • Accurate kinetic parameters are vital for the reliable application of activated sludge models in wastewater treatment.
  • Existing methods for parameter estimation may lack efficiency or accuracy across diverse environmental conditions.
  • The Activated Sludge Model No. 1 (ASM1) is a widely used tool, but its predictive power depends heavily on precise parameter values.

Purpose of the Study:

  • To propose and evaluate an improved cuckoo search (ICS) algorithm for estimating kinetic parameters in the Activated Sludge Model No. 1 (ASM1).
  • To enhance the speed and accuracy of global optimization for kinetic parameter estimation.
  • To validate the performance of the ICS algorithm using practical wastewater treatment field data.

Main Methods:

  • Development of an improved cuckoo search (ICS) algorithm incorporating cyclical adjustment strategy and adaptive step size adjustment.
  • Testing the ICS algorithm's global search capability on six standard benchmark functions.
  • Application of the ICS algorithm to estimate seven sensitive kinetic parameters within the ASM1 framework.
  • Validation of the ASM1 model with estimated parameters against real-world field data.

Main Results:

  • The ICS algorithm demonstrated enhanced searching ability and adaptive optimization capabilities.
  • ICS proved effective in accurately estimating the seven sensitive kinetic parameters for ASM1.
  • Wastewater treatment process predictions using ASM1 with ICS-estimated parameters showed improved accuracy compared to predictions with unadjusted parameters.
  • The model's predictions more closely aligned with actual field data after parameter adjustment.

Conclusions:

  • The improved cuckoo search (ICS) algorithm offers a robust and efficient method for estimating kinetic parameters in the Activated Sludge Model No. 1 (ASM1).
  • Accurate kinetic parameter estimation significantly enhances the predictive accuracy of wastewater treatment models.
  • This approach is valuable for optimizing wastewater treatment processes under varying environmental conditions.