Predictive control with multiobjective optimization: Application to a sludge drying operation. (12th July 2015)

• Record Type: Journal Article
• Authors: Fuentes, A.; Ploteau, J.P.; Glouannec, P.
• Is Part Of: Computers & chemical engineering. Volume 78(2015)
• Page Start: 70
• Page End: 78
• Publication Date: 2015-07-12
• Subjects: Offline predictive control -- Multiobjective optimization -- Multiphysics modeling -- Operating input parameters; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2015.04.017
• Languages: English
• ISSNs: 0098-1354

Abstract

Graphical abstract: Highlights: A predictive command strategy with a multiobjective optimization problem is proposed. The procedure is used to found an optimal command policy for the air drying conditions. A multiphysics model is validated for the drying step with a reversal operation. An energetic analysis of the improvement is proposed. Abstract: The main objective of this study is to develop an offline tuning of the operating input parameters for a sludge drying operation, by using multiobjective optimization techniques combined with a predictive control method. The manipulated variables concerned are the temperature and the relative humidity of the drying air ( T air, RHair ). The optimal time for the reversal operation of the product is also investigated. The optimization procedure is coupled to a one-dimensional numerical model that allows the simulation of moisture content and temperature field evolutions in the product during the drying step. A genetic algorithm is used to identify the two manipulated variables, at each step time, by minimizing simultaneously three objective functions over a finite horizon. These objective functions are linked to penalties concerning the heating and dehumidifying of the outside air used for the drying stage and to a global moisture content gap relative to a drying target. First, the heat and mass transfer model is validated for the drying step of a plate sample of sludge, with a reversal operation. Afterwards, the optimization procedure is carried out, and the results are discussed in terms of an energetic analysis.