Abstract
High-performance control design for a flexible space structure is challenging as highfidelity plant models are difficult to obtain a priori. Uncertainty in the control design models typically require a very robust, low-performance control design, which must be tuned onorbittoachievetherequiredperformance.Closed-loopsystemidentificationisoftenrequired to obtain a multivariable open-loop plant model based on closed-loop response data. 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 used to mitigate the nonuniqueness and overparameterization of general state space realizations. This controlrelevant system identification procedure stresses the joint nature of the system identification and control design problem by seeking to obtain a model that minimizes the difference between the predicted and actual closed-loop performance.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Aerospace Computing, Information, and Communication
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
