Cognition-Oriented Quadratic Stabilization of Unknown Nonlinear Systems

A Data-Driven Quadratic Stability Criterion and its Application

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This thesis focuses on developing a cognition-oriented robust controller to realize quadratic stabilization of unknown nonlinear systems. The core of the proposed control relies on a data-driven stability criterion, which is established according to the geometric interpretation of the quadratic Lyapunov stability condition. By properly arranging soft-computing techniques and the proposed stability criterion within a cognitive framework serving as basic cognitive functions and expert knowledge base, respectively, the proposed method can build the internal representation of the knowledge about the quadratic stability and the dynamics of the current motion of the system to be controlled. Based on these representations, suitable control input can be generated by the planning module of the proposed controller to stabilize the motion of the unknown systems. Due to these reasons, the propose controller can be classified into cognitive approaches. At the end of this thesis two numerical examples are shown to demonstrate the successful application and performance of the proposed control method.
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Dokumententyp:
Wissenschaftliche Abschlussarbeiten » Dissertation
Fakultät / Institut:
Fakultät für Ingenieurwissenschaften » Maschinenbau und Verfahrenstechnik » Institut für Mechatronik und Systemdynamik
Dewey Dezimal-Klassifikation:
600 Technik, Medizin, angewandte Wissenschaften » 620 Ingenieurwissenschaften
Beitragende:
Univ.-Prof. Dr.-Ing. Söffker, Dirk [Betreuer(in), Doktorvater]
Univ.-Prof. Dr.-Ing. Raisch, Jörg [Gutachter(in), Rezensent(in)]
Sprache:
Englisch
Kollektion / Status:
Dissertationen / Dokument veröffentlicht
Datum der Promotion:
10.10.2011
Dokument erstellt am:
20.12.2011
Promotionsantrag am:
14.07.2011
Dateien geändert am:
20.12.2011
Medientyp:
Text