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Closed Loop System Identification with Genetic AlgorithmsHigh performance control design for a flexible space structure is challenging since high fidelity plant models are di.cult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. Closed loop system identi.cation is often required to obtain a multivariable open loop plant model based on closed-loop response data. In order to provide an accurate initial plant model to guarantee convergence for standard local optimization methods, this paper presents a global parameter optimization method using genetic algorithms. A minimal representation of the state space dynamics is employed to mitigate the non-uniqueness and over-parameterization of general state space realizations. This control-relevant system identi.cation procedure stresses the joint nature of the system identi.cation and control design problem by seeking to obtain a model that minimizes the di.erence between the predicted and actual closed-loop performance.
Document ID
20040139305
Acquisition Source
Marshall Space Flight Center
Document Type
Preprint (Draft being sent to journal)
Authors
Whorton, Mark S.
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Date Acquired
September 7, 2013
Publication Date
January 1, 2004
Subject Category
Numerical Analysis
Meeting Information
Meeting: AIAA/GN and C Conference
Location: Providence, RI
Country: United States
Start Date: August 15, 2004
End Date: August 19, 2004
Sponsors: American Inst. of Aeronautics and Astronautics
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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