Model predictive control in fermentation process – A review
Wan Ying Chai, Kenneth Tze Kin Teo, Min Keng Tan, Heng Jin Tham
Abstract
Fermentation process, in the aspect of industrial field, is defined as the involvement of microbes in mass production of valuable products. Microorganisms can produce complex compound which is difficult and costly to obtain through chemical synthesis. Also, bioprocess brings less negative impact towards the environment. However, microorganisms are very sensitive to their surroundings, particularly pH, temperature, oxygen amount and type of nutrients. Therefore, optimal operational control becomes the concern of biomanufacturing industries to promote the microbial growth and metabolic activity for maximum desired product formation and prohibit any possible by-product yield. Model predictive control (MPC) has been studied extensively in regulating fermentation process. It is an advanced control approach which performs prediction on a sequence of future output response and take optimal control action according to objective function. Earlier remedy can be performed as problem is detected earlier through the future prediction. This paper reviews the application of MPC in different fermentation process with different selection of the manipulated and controlled variables. Basic concept of MPC strategy is also presented, together with the development of MPC application in fermentation over the years.