LFT-LPV Modeling and Control of a Control Moment Gyroscope

C. Hoffmann; H. Werner

doi:10.1109/CDC.2015.7403053

LFT-LPV Modeling and Control of a Control Moment Gyroscope

C. Hoffmann, H. Werner

Hamburg University of Technology

12 Citations (Scopus)

Abstract

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 language	English
Title of host publication	2015 54th IEEE Conference on Decision and Control (CDC)
Number of pages	6
Publisher	IEEE
Publication date	08.02.2015
Pages	5328-5333
Article number	7403053
ISBN (Print)	978-1-4799-7884-7, 978-1-4799-7885-4
ISBN (Electronic)	978-1-4799-7886-1
DOIs	https://doi.org/10.1109/CDC.2015.7403053
Publication status	Published - 08.02.2015
Event	54th IEEE Conference on Decision and Control - Osaka International Convention Center (Grand Cube), Kita-KuOsaka, Japan Duration: 15.12.2015 → 18.12.2015 Conference number: 119391

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title = "LFT-LPV Modeling and Control of a Control Moment Gyroscope",

abstract = "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.",

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AU - Werner, H.

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N2 - 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.

AB - 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.

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ER -

LFT-LPV Modeling and Control of a Control Moment Gyroscope

Abstract

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