Detailseite
Projekt Druckansicht

Extremwertregelung für dynamische Abbildungen: Ein Zugang mittels Lie Klammern

Fachliche Zuordnung Automatisierungstechnik, Mechatronik, Regelungssysteme, Intelligente Technische Systeme, Robotik
Förderung Förderung von 2015 bis 2022
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 272118942
 
Erstellungsjahr 2021

Zusammenfassung der Projektergebnisse

The main goal of the project was the development of novel extremum seeking algorithms for dynamic maps based on Lie bracket averaging (or Lie bracket approximation) methods. Extremum seeking control is a powerful methodology to solve various control problems without the need of a detailed system model. There exist different approaches to analyze and design extremum seeking algorithms for dynamic maps (dynamical systems). The most common approach is based on classical averaging theory. In this project, we developed an alternative and novel approach based on Lie bracket approximation ideas. In particular, the goal was to develop an analysis and design framework which can cope with dynamic maps (dynamical systems) and which allows to incorporate constraints and system models in order to improve the performance of extremum seeking control loops. In the course of the project, we established several novel results. One important achievement was to fully incorporate dynamic maps in the Lie bracket framework. Hereby, we developed two approaches. The first approach goes along the lines of classical averaging theory, while the second is based on the Chen-Fliess series expansion. Both approaches are model-free and can deal with unknown dynamic maps. In applications, often some knowledge about the to-be-controlled system is available. In the course of the project, we were able to integrate such partial knowledge of the system in terms of state space models into the analysis and design of extremum seeking algorithms. For example, with the methods developed in the project, it is now possible do design extremum seeking algorithms for systems which are composed by a feedback-linearizable system, where a state space model is known, in conjunction with an unknown dynamic map. Finally, we also improved the performance of extremum seeking algorithms in the project. We could significantly improve the performance of Lie bracket based extremum seeking algorithms, by developing a whole class of novel algorithms which exploit the generality (non-uniqueness) of approximating gradients in terms of Lie bracket vector fields. These algorithms showed a significant better performance, in simulation and in experiments, than the standard approach. Overall, we believe that the established results in the project contribute significantly to the area of extremum seeking control. The obtained results have turned the Lie bracket based extremum seeking approach into a powerful and flexible methodological toolkit that can be flexibly applied to solve a wide variety of control problems.

Projektbezogene Publikationen (Auswahl)

 
 

Zusatzinformationen

Textvergrößerung und Kontrastanpassung