Modeling of an Irrigation Main Canal Pool based on a NARX-ANN System Identification
Dynamic models of main irrigation canals are necessary to carry out real-time canal flow control and supervision. Since the hydraulic equations of canal dynamics are nonlinear, their solution involves large computations that impede their use in real-time applications. Then these tasks are often impl...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad de Castilla-La Mancha |
| Repositorio: | RUIdeRA. Repositorio Institucional de la UCLM |
| OAI Identifier: | oai:ruidera.uclm.es:10578/40071 |
| Acceso en línea: | https://hdl.handle.net/10578/40071 |
| Access Level: | acceso abierto |
| Palabra clave: | Artificial neural network Nonlinear systems identification |
| Sumario: | Dynamic models of main irrigation canals are necessary to carry out real-time canal flow control and supervision. Since the hydraulic equations of canal dynamics are nonlinear, their solution involves large computations that impede their use in real-time applications. Then these tasks are often implemented using simple local linear models obtained around an operating point, that are unable to capture the dynamics when large canal operation changes happen. |
|---|