Fuzzy logic control and soft sensing applications in food and beverage processes

Biotechnological processes – particularly fermentation processes - play a very important technological an economical role for the production steps in the food and beverage sector. In order to ensure constantly high product quality combined with efficient manufacturing, intelligent control systems and strategies are required. However, biosystems contain living organisms and therefore underlie particular process dynamics such as nonlinear and time-varying behavior. Furthermore, initial process conditions cannot be kept constant and therefore precise process reproducibility hardly can be achieved. On that account these multivariate systems put high requirements to the practical on-line observation, control, monitoring and prediction of significant process key parameters whose acquirement is of crucial importance for a comprehensive understanding and control of the process. During the last decades great efforts have been undertaken to cope with those challenges by means of intelligent soft computing and reveal great opportunities to integrate human expertise and learning procedures for improved process control strategies of biological systems. Particularly fuzzy logic based control systems show high potential to manage the complex production processes and to deal with fragmental process information. This review critically presents the chances as well as the limitations of fuzzy and hybrid expert system approaches in food and beverage process control from a theoretical and application based point of view.     «

Biotechnological processes – particularly fermentation processes - play a very important technological an economical role for the production steps in the food and beverage sector. In order to ensure constantly high product quality combined with efficient manufacturing, intelligent control systems and strategies are required. However, biosystems contain living organisms and therefore underlie particular process dynamics such as nonlinear and time-varying behavior. Furthermore, initial process con...     »