Development of a control system using the fuzzy set theory applied to a browning process––towards a control system of the browning process combining a diagnosis model and a decision model––part II

Abstract In the food industry, controlling sensory properties on the manufacturing line represents a key issue for companies, because sensory properties influence consumer choice and preference. Browning quality is difficult to control because of the variability of the products treated by the browning process. In this paper, we propose a decision model developed with the Takagi–Sugeno method. It provides the actions to be performed on the actuators of the browning oven by using measurements of the browning variable obtained by the diagnosis model described in part I. The combination of the two models provides a control system that improves the browning quality of food products. The decision model was validated on a database with 90% compatibility with operator action at a sensitivity level of 2% on the actuators. The control system was then validated by operation on the manufacturing line for 180 min.