Dynamic optimization of low-pressure carburizing furnaces
| Autor: | Fatima Matamoros Marin, Roda Bounaceur, Pierre-Alexandre Glaude, Hubert Monnier, Abderrazak M. Latifi |
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| Přispěvatelé: | Institut national de recherche et de sécurité (Vandoeuvre lès Nancy) (INRS ( Vandoeuvre lès Nancy)), Laboratoire Réactions et Génie des Procédés (LRGP), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
State variable
Optimization problem 0211 other engineering and technologies 02 engineering and technology 021001 nanoscience & nanotechnology 7. Clean energy Carburizing [CHIM.GENI]Chemical Sciences/Chemical engineering Dimension (vector space) Control theory Ordinary differential equation Process control Diffusion (business) 0210 nano-technology ComputingMilieux_MISCELLANEOUS 021102 mining & metallurgy Mathematics Sequential quadratic programming |
| Zdroj: | 2021 23rd International Conference on Process Control (PC) 2021 23rd International Conference on Process Control (PC), Jun 2021, Strbske Pleso, France. pp.72-77, ⟨10.1109/PC52310.2021.9447496⟩ |
| DOI: | 10.1109/PC52310.2021.9447496⟩ |
| Popis: | This paper presents the modelling and dynamic optimization of low pressure carburizing of steel. A cyclic hybrid model alternating two modes, i.e. the two stages of the process, boost and diffusion stages, is proposed. Each mode is characterized by a set of ordinary differential equations and its corresponding transition conditions and transition functions. The subsequent dynamic optimization problem is formulated and it aims to minimize the production of toxic compounds. The decision variables selected are the operating conditions, i.e. the lengths of boost and diffusion stages as well as the inlet flowrate of carburizing gas. Equality and inequality constraints are added on the state variables to ensure the quality of the treated steel parts. The resulting optimization problem of infinite dimension is transformed into a finite-dimension problem by means of the control vector parameterization approach and solved using a gradient-based method, i.e. sequential quadratic programming method. The solution algorithm is tested on an example and the optimal profiles yield satisfactory results. |
| Databáze: | OpenAIRE |
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