Nonlinear Constrained Predictive Control of dissolved oxygen in bio-reactor

Abstract

A nonlinear constrained model predictive control (NCMPC) method is presented for the control of the dissolved oxygen in a bio-reactor system using Hammerstein model. The control of dissolved oxygen as output is accomplished by adjusting the stirrer speed as input. The proposed controller is compared with the Nonlinear Model Predictive Control(NMPC) method without input constraints. The simulations and experiments are implemented. A control system based on microprocessor PIC16F877 is developed to implement the experiments. The simulation and experimental results show that the performance of the input stirrer speed with input constraints is better than that without input constraints. The effectiveness of the proposed controller is shown through simulations under the known disturbance and variable set-point tracking.