Prediction-based sampled-data controller design for attitude stabilisation of a rigid spacecraft with disturbances
Baolong Zhu,
Zhiping Zhang,
Ding Zhou,
Jie Ma and
Shunli Li
International Journal of Systems Science, 2017, vol. 48, issue 11, 2356-2367
Abstract:
This paper investigates the H∞ control problem of the attitude stabilisation of a rigid spacecraft with external disturbances using prediction-based sampled-data control strategy. Aiming to achieve a ‘virtual’ closed-loop system, a type of parameterised sampled-data controller is designed by introducing a prediction mechanism. The resultant closed-loop system is equivalent to a hybrid system featured by a continuous-time and an impulsive differential system. By using a time-varying Lyapunov functional, a generalised bounded real lemma (GBRL) is first established for a kind of impulsive differential system. Based on this GBRL and Lyapunov functional approach, a sufficient condition is derived to guarantee the closed-loop system to be asymptotically stable and to achieve a prescribed H∞ performance. In addition, the controller parameter tuning is cast into a convex optimisation problem. Simulation and comparative results are provided to illustrate the effectiveness of the developed control scheme.
Date: 2017
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2017.1316883 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:48:y:2017:i:11:p:2356-2367
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20
DOI: 10.1080/00207721.2017.1316883
Access Statistics for this article
International Journal of Systems Science is currently edited by Visakan Kadirkamanathan
More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().