Publicação
Assessment of data-driven modeling strategies for water delivery canals
| Resumo: | The aim of this work is to develop nonlinear dynamical models for the canal system of Núcleo de Hidráulica e Controlo de Canais. The canal is a nonlinear system and thus should be modeled to meet given operational requirements, while capturing all relevant system dynamics, such as the resonance waves created due to the movements of gates, and also contributing to the controller precision. The nonlinear modeling is based on data-driven methods, namely Composite Local Linear Models, Fuzzy Models and Artificial Neural Networks. These models are identified using data collected from the experimental facility, and their performance is assessed based on suitable validation criteria. The modeling results show the effectiveness of these models while capturing all significant dynamics for the canal system. |
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| Autores principais: | Tavares, Isaías |
| Outros Autores: | Borges, José; Gonçalves Cavaco Mendes, Mário José; Ayala Botto, Miguel |
| Assunto: | Nonlinear modeling Water canal system Composite local linear models Fuzzy models Artificial neural networks |
| Ano: | 2012 |
| País: | Portugal |
| Tipo de documento: | documento de conferência |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Instituto Politécnico de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Científico do Instituto Politécnico de Lisboa |
| Resumo: | The aim of this work is to develop nonlinear dynamical models for the canal system of Núcleo de Hidráulica e Controlo de Canais. The canal is a nonlinear system and thus should be modeled to meet given operational requirements, while capturing all relevant system dynamics, such as the resonance waves created due to the movements of gates, and also contributing to the controller precision. The nonlinear modeling is based on data-driven methods, namely Composite Local Linear Models, Fuzzy Models and Artificial Neural Networks. These models are identified using data collected from the experimental facility, and their performance is assessed based on suitable validation criteria. The modeling results show the effectiveness of these models while capturing all significant dynamics for the canal system. |
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