Techniques for the systematic modeling and Linear Parameter-Varying (LPV) control of highly nonlinear plants are proposed and applied to a four-degree of freedom (4-DOF) Control Moment Gyroscope (CMG). First, the factorization problem to yield LPV representations from general nonlinear models is formalized and tractable heuristics are proposed. Based on these, LPV parameter sets are automatically derived via a Principle Component Analysis (PCA)-based method that only requires model coefficients and allows straightforward approximation. Improved State-Feedback (SF) controller synthesis conditions for descriptor Linear Fractional Transformation (LFT)-LPV models are proposed that significantly reduce the synthesis effort. Both approximate and exact controller syntheses yield high performance in the entire operating envelope and are validated by experiments.

Original languageEnglish
Title of host publication2015 54th IEEE Conference on Decision and Control (CDC)
Number of pages6
Publication date08.02.2015
Article number7403053
ISBN (Print)978-1-4799-7884-7, 978-1-4799-7885-4
ISBN (Electronic)978-1-4799-7886-1
Publication statusPublished - 08.02.2015
Event54th IEEE Conference on Decision and Control - Osaka International Convention Center (Grand Cube), Kita-KuOsaka, Japan
Duration: 15.12.201518.12.2015
Conference number: 119391


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