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Neural Network Model Predictive Control of a Wastewater Treatment Bioprocess

  • Dorin Şendrescu
  • Emil Petre
  • Dan Popescu
  • Monica Roman
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 10)

Abstract

This paper deals with the design of a nonlinear model predictive control (NMPC) scheme for the regulation of the acetate concentration in a biomethanation process – wastewater biodegradation with production of methane gas that takes place inside a Continuous Stirred Tank Bioreactor. The NMPC control structure is based on a radial basis function neural network used as on-line approximator to learn the nonlinear characteristics of process. Minimization of the cost function is realised using the Levenberg–Marquardt numerical optimisation method. Some simulation results are given to illustrate the efficiency of the proposed control strategy.

Keywords

Nonlinear systems Neural networks Model predictive control Wastewater treatment bioprocesses 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Dorin Şendrescu
    • 1
  • Emil Petre
    • 1
  • Dan Popescu
    • 1
  • Monica Roman
    • 1
  1. 1.Department of Automatic ControlUniversity of CraiovaCraiovaRomania

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