Softly Switched Robustly Feasible Model Predictive Control for Nonlinear Network Systems - Publikacja - MOST Wiedzy

Wyszukiwarka

Softly Switched Robustly Feasible Model Predictive Control for Nonlinear Network Systems

Abstrakt

It is common that an efficient constrained plant operation under full range of disturbance inputs require meeting different sets of control objectives. This calls for application of model predictive controllers each of them being best fit into specific operating conditions. It further requires that not only designing robustly feasible model predictive controllers is needed to satisfy the real plant state/output constraints, but also a switching mechanism between these controllers during the operation is inevitable. A simple hard switching may introduce unwanted transients and more importantly may not achieve robustly feasible controller operation. In this paper, the soft switching method for nonlinear systems that allows switching between robustly feasible model predictive controllers is presented. The algorithm for the fast switching method is also addressed for the switching mechanism parameter design that minimizes that switching time duration. The method is illustrated by the application to hydraulic optimizing control in the Drinking Water Distribution Systems example.

Cytuj jako

Pełna treść

pełna treść publikacji nie jest dostępna w portalu

Słowa kluczowe

Informacje szczegółowe

Kategoria:
Aktywność konferencyjna
Typ:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Tytuł wydania:
Large Scale Complex Systems Theory and Applications. vol. 13, part 1 strony 200 - 205
Język:
angielski
Rok wydania:
2013
Opis bibliograficzny:
Brdyś M., Vu Nam T.: Softly Switched Robustly Feasible Model Predictive Control for Nonlinear Network Systems// Large Scale Complex Systems Theory and Applications. vol. 13, part 1/ ed. Xi, Yugeng Shanghai Jiao Tong University, Shanghai, China: Elsevier, 2013, s.200-205
Weryfikacja:
Politechnika Gdańska

wyświetlono 105 razy

Publikacje, które mogą cię zainteresować

Meta Tagi