Advanced Temperature Control Applied on An Industrial Box Furnace

Author:

Tudon-Martinez Juan C.1,Lozoya-Santos Jorge de-J.2,Cantu-Perez Alberto34,Cardenas-Romero Andrea4

Affiliation:

1. School of Engineering and Technology, University of Monterrey, San Pedro Garza García, Nuevo León 66238, Mexico

2. Tecnologico de Monterrey, Monterrey, Nuevo León 66359, Mexico

3. University of Monterrey, San Pedro Garza García, Nuevo León 66359, Mexico;

4. Nutec Bickley, S.A. De C.V., Santa Catarina, Nuevo León 66359, Mexico

Abstract

Abstract The current control system of an industrial box furnace usually uses a proportional-integral-derivative (PID) controller. Typically, this control system requires on-site tuning and specific heuristic knowledge, such that the furnace can have acceptable performance but not optimal. However, by using a proper model in the operating range of the furnace from the designing phase, it can be designed a more efficient control system capable to reach better performance in this industrial process. In this sense, the main objective of this paper is the design and validation of an advanced control strategy in the early design stage of an industrial box furnace. The goals are to decrease the controller tuning time during the furnace commissioning process, improve the furnace performance with respect to classical industrial controllers, and decrease the system energy expenses. Thus, a comparative analysis in a simulated environment has been carried out between the performance of a PID controller by its typical industrial use, a model predictive control (MPC) due to the optimal results in similar industrial processes, and a virtual reference feedback tuning (VRFT) control by its feasibility of implementation. Results show that the advanced MPC and VRFT controllers are more efficient in the used fuel/gas than the PID. MPC shows the best balance between performance and actuation, it improves the control performance up to 87.2% with respect to the VRFT controller.

Funder

Consejo Nacional de Ciencia y Tecnología

Publisher

ASME International

Subject

Fluid Flow and Transfer Processes,General Engineering,Condensed Matter Physics,General Materials Science

Reference37 articles.

1. Application of Sliding Modes to the Control of Industrial Furnaces;Edwards,1994

2. Comparison of Predictive Control Methods for High Consumption Industrial Furnace;Stojanovski;Sci. World J.,2013

3. Fuzzy Logic Control of Industrial Heat Treatment Furnaces;Sobol,1999

4. Nonlinear Dynamic Simulation and Control of Large- Scale Reheating Furnace Operations Using a Zone Method Based Model;Hu;Appl. Therm. Eng.,2018

5. A Survey of Industrial Model Predictive Control Technology;Qin;Control Eng. Pract.,2003

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