This work is done in collaboration with Prof. Felice Andrea Pellegrino and Prof. Gianfranco Fenu of the University of Trieste, my colleague Ph.D. Francesco Forte and my place of work in the AD\&T Laboratory at Electrolux Professional Group. The purpose of this research is the design of a control system with the aim of improving the performance of professional appliances dedicated to the food processing in order to meet the objectives of energy saving and culinary quality. Furthermore, it is necessary to design real-time control software that is able to predict the behavior of the device, estimate non-measurable physical quantities, respect the constraints on energy consumption imposed a priori, reduce the effect of delay response with the aim of having smarter and more robust solutions. Therefore, we apply the model predictive control (MPC) strategy in an industrial setting, specifically for controlling the temperature of Oven Professional Appliances. The workflow includes identifying and validating a model of the cell temperature and incorporating disturbance models. MPC is implemented using a state-space formulation. The proposed method shows significant energy saving and error tracking reduction with respect to the current oven control; its effectiveness has been demonstrated through several tests carried out on a professional oven.
This work is done in collaboration with Prof. Felice Andrea Pellegrino and Prof. Gianfranco Fenu of the University of Trieste, my colleague Ph.D. Francesco Forte and my place of work in the AD\&T Laboratory at Electrolux Professional Group. The purpose of this research is the design of a control system with the aim of improving the performance of professional appliances dedicated to the food processing in order to meet the objectives of energy saving and culinary quality. Furthermore, it is necessary to design real-time control software that is able to predict the behavior of the device, estimate non-measurable physical quantities, respect the constraints on energy consumption imposed a priori, reduce the effect of delay response with the aim of having smarter and more robust solutions. Therefore, we apply the model predictive control (MPC) strategy in an industrial setting, specifically for controlling the temperature of Oven Professional Appliances. The workflow includes identifying and validating a model of the cell temperature and incorporating disturbance models. MPC is implemented using a state-space formulation. The proposed method shows significant energy saving and error tracking reduction with respect to the current oven control; its effectiveness has been demonstrated through several tests carried out on a professional oven.
Advanced Model Predictive Control Solutions for Performance Enhancement of Food Service Appliances / Castellino, JUAN MARCELO. - (2024 Feb 02).
Advanced Model Predictive Control Solutions for Performance Enhancement of Food Service Appliances
CASTELLINO, JUAN MARCELO
2024-02-02
Abstract
This work is done in collaboration with Prof. Felice Andrea Pellegrino and Prof. Gianfranco Fenu of the University of Trieste, my colleague Ph.D. Francesco Forte and my place of work in the AD\&T Laboratory at Electrolux Professional Group. The purpose of this research is the design of a control system with the aim of improving the performance of professional appliances dedicated to the food processing in order to meet the objectives of energy saving and culinary quality. Furthermore, it is necessary to design real-time control software that is able to predict the behavior of the device, estimate non-measurable physical quantities, respect the constraints on energy consumption imposed a priori, reduce the effect of delay response with the aim of having smarter and more robust solutions. Therefore, we apply the model predictive control (MPC) strategy in an industrial setting, specifically for controlling the temperature of Oven Professional Appliances. The workflow includes identifying and validating a model of the cell temperature and incorporating disturbance models. MPC is implemented using a state-space formulation. The proposed method shows significant energy saving and error tracking reduction with respect to the current oven control; its effectiveness has been demonstrated through several tests carried out on a professional oven.File | Dimensione | Formato | |
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PhD_Thesis_CastellinoJM.pdf
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