Modelling and uncertainties characterization for robust control
In this work, multi-input multi-output (MIMO) process identification is studied, where the model identification is dedicated to the control design goal. An ad hoc identification procedure is presented which allows estimating not only a nominal parametric process model, but also a bound of the model...
| Autores: | , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | Argentina |
| Recursos: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/1339 |
| Acesso em linha: | http://hdl.handle.net/11336/1339 |
| Access Level: | acceso abierto |
| Palavra-chave: | NONLINEAR IDENTIFICATION ROBUST CONTROL UNCERTAINTY CHARACTERIZATION https://purl.org/becyt/ford/2.2 https://purl.org/becyt/ford/2 |
| Resumo: | In this work, multi-input multi-output (MIMO) process identification is studied, where the model identification is dedicated to the control design goal. An ad hoc identification procedure is presented which allows estimating not only a nominal parametric process model, but also a bound of the model uncertainty (i.e. modelling errors). The model structure is defined in a way that the identified nominal model and the uncertainties can readily be used for the analysis and design of a robust control system by means of many of the techniques available in the literature. Simulation examples are given to illustrate the method. |
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