Advanced Temperature Control Applied on An Industrial Box Furnace

Juan C. Tudon-Martinez*, Jorge De J. Lozoya-Santos, Alberto Cantu-Perez, Andrea Cardenas-Romero

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Article number061001 EN
JournalJournal of Thermal Science and Engineering Applications
Volume14
Issue number6
DOIs
Publication statusPublished - 1 Jun 2022

Bibliographical note

Funding Information:
Authors thank CONACyT for the partial financial support in the Project PEI number 250460.

Publisher Copyright:
© 2021 BMJ Publishing Group. All rights reserved.

All Science Journal Classification (ASJC) codes

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

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