Intelligent Predictive Control - Application to Scheduled Crystallization Processes

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2009

Autores

Luis Alberto Paz Suárez (Autor) FEUP; Petia Georgieva (Autor) FEUP; Sebastião Feyo de Azevedo (Autor) FEUP

Ata de Conferência Internacional

Título: 2009 International Conference on Adaptive and Intelligent Systems

Páginas: 160-165

International Conference on Adaptive and Intelligent Systems

Klagenfurt, Austria, 24-26 September 2009

Indexação

Scopus

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia química

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia química

Outras Informações

Abstract (EN): The purpose of this paper is twofold. On one hand, we propose a modification of the general Model Predictive Control (MPC) approach where a prespecified tracking error is tolerated. The introduction of error tolerance (ET) in the MPC optimization algorithm reduces considerably the average duration of each optimization step and makes the MPC computationally more efficient and attractive for industrial applications. On the other hand a challenging scheduled crystallization process serves as a case study to show the practical relevance of the new intelligent predictive control. Comparative tests with different control policies are performed: i) Classical MPC with analytical or Artificial Neural Network (ANN) process model; ii) ET MPC with analytical or ANN process model; iii) Proportional-Integral (PI) control. Besides the computational benefits of ET MPC, the integration of ANN into the ET MPC brings substantial improvements of the final process performance measures and further relaxes the computational demands.

Idioma: Inglês

Tipo (Avaliação Docente): Científica