Abstract
Driven by the perspective of fossil fuels depletion, the concerns about energy security and global warming, the promotion of biofuels as energy for transportation in the world has become a popular trending. Bioethanol is one of a potential biofuel with a high octane number and has replaced lead as an octane enhancer in petrol. In bioethanol fermentation, the process possesses complex dynamics caused by the microorganisms involved in the process as well as the variation in the biomass composition with the operating conditions. In this work, a nonlinear model known as the Nonlinear Autoregressive with Exogenous input (NARX) model was developed and embedded with a nonlinear programming (NLP) optimizer in the Model Predictive Control (MPC) strategy (NARX-MPC) to control the fermentation process. Then, the performance of the NARX-MPC was evaluated and compared with the Linear model based MPC (LMPC) in set point tracking, disturbance rejections and robustness tests. From all tests carried out, NARX-MPC has shown better performances as compared to LMPC.
