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Recent Applications of Advanced Control Techniques in Food Industry

Kondakci, Turkay, Zhou, Weibiao
Food and bioprocess technology 2017 v.10 no.3 pp. 522-542
baking, brewing, controllers, drying, fermentation, food industry, food quality, fuzzy logic, neural networks, process control, raw materials
Process control has become increasingly important for the food industry since the last decades due to its capability of increasing yield, minimizing production cost, and improving food quality. New developments for control strategies such as artificial neural networks and model-based controls as well as their applications have brought several new prospects to the food industry. Food processes are mostly nonlinear and show different process dynamics with various raw materials and different processing conditions. Therefore, advanced process control techniques are highly invaluable compared to classical control approaches. In this review, advanced control strategies, particularly model-based controllers, fuzzy logic controllers, and neural network-based controllers, are firstly described with their main characteristics. A number of applications of the advanced control strategies are then discussed according to different food processing industries such as baking, drying, fermentation/brewing, dairy, and thermal/pressure food processing.