Comparing multivariable uncertain model structures for data‐driven robust control: Visualization and application to a continuously variable transmission
-
Published:2023-07-03
Issue:16
Volume:33
Page:9636-9664
-
ISSN:1049-8923
-
Container-title:International Journal of Robust and Nonlinear Control
-
language:en
-
Short-container-title:Intl J Robust & Nonlinear
Author:
Tacx Paul1ORCID,
Oomen Tom12
Affiliation:
1. Control Systems Technology, Department of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands
2. Delft Center for Systems and Control, Faculty of Mechanical, Maritime, and Materials Engineering Delft University of Technology Delft The Netherlands
Abstract
AbstractThe selection of uncertainty structures is an important aspect of system identification for robust control. The aim of this paper is to provide insight into uncertain multivariable systems for robust control. A unified method for visualizing model sets is developed by generating Bode plots of multivariable uncertain systems, both in magnitude and phase. In addition, these model sets are compared from the viewpoint of the control objective, allowing a quantitative analysis as well. An experimental case study on an automotive transmission application demonstrates these connections and confirms the importance of the developed framework for control applications. In addition, the experimental results provide new insights into the shape of associated model sets by using the presented visualization procedure. Both the theoretical and experimental results confirm that a recently developed robust‐control‐relevant uncertainty structure outperforms general dual‐Youla‐Kučera uncertainty, which in turn outperforms traditional uncertainty structures, including additive uncertainty.
Funder
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Subject
Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanical Engineering,Aerospace Engineering,Biomedical Engineering,General Chemical Engineering,Control and Systems Engineering