Analysis of control methods for thermal processing of canned fruits and vegetables in vertical autoclaves

Abstract

The paper examines the features of the process of heat treatment of canned fruits and vegetables in vertical autoclaves aimed at preserving their quality and safety for a long time. An analysis of existing methods of controlling the processes of heat treatment of canned fruits and vegetables in vertical autoclaves is carried out. The problems of using traditional proportional-integral-differential (PID) controllers are considered, due to the significant thermal inertia of the object and the complexity of setting it up for different types and masses of loading. Promising approaches to automation are analyzed, in particular model-based predictive control (MPC), which allows optimizing the process directly according to the target indicator of accumulated microbiological lethality (F0) taking into account technological limitations. Special attention is paid to the possibilities of using intelligent methods, such as adaptive fuzzy controllers (Fuzzy-PID) and artificial neural networks (ANN), which perform the function of virtual "soft sensors" for predicting the temperature inside the container. It was found that the use of standard algorithms for such products leads to significant errors in the calculations of accumulated lethality and, as a result, to thermal damage to raw materials (digestion). The results of the analysis substantiate the need to transition to hybrid intelligent control systems to ensure energy efficiency, compensate for the nonlinearity of heat exchange processes and preserve the nutritional value of complex heterogeneous products.