Neural network model predictive control of a wastewater treatment bioprocess

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. © 2011 Springer-Verlag Berlin Heidelberg.