Sampled-data model predictive control for nonlinear time-varying systems: Stability and robustness

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2007

Autores

fontes, facc (Autor) Outra; magni, l (Autor) Outra; gyurkovics, e (Autor) Outra

Ata de Conferência Internacional

Título: Assessment and Future Directions of Nonlinear Model Predictive Control

Páginas: 115-129

International Workshop on Assessment and Future Directions of Nonlinear Model Predictive Control

Freudenstadt Lauterbad, GERMANY, AUG 26-30, 2005

Indexação

ISI Web of Knowledge - 15 Citações

Scopus - 19 Citações

Outras Informações

ID Authenticus: P-004-CJV

DOI: 10.1007/978-3-540-72699-9_9

Abstract (EN): We describe here a sampled-data Model Predictive Control framework that uses continuous-time models but the sampling of the actual state of the plant as well as the computation of the control laws, are carried out at discrete instants of time. This framework can address a very large class of systems, nonlinear, time-varying, and nonholonomic. As in many others sampled-data Model Predictive Control schemes, Barbalat's lemma has an important role in the proof of nominal stability results. It is argued that the generalization of Barbalat's lemma, described here, can have also a similar role in the proof of robust stability results, allowing also to address a very general class of nonlinear, time-varying, nonholonomic systems, subject to disturbances. The possibility of the framework to accommodate discontinuous feedbacks is essential to achieve both nominal stability and robust stability for such general classes of systems.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 15