http://iet.metastore.ingenta.com
1887

Design and input-to-state practically stable analysis of the mixed H2/H feedback robust model predictive control

Design and input-to-state practically stable analysis of the mixed H2/H feedback robust model predictive control

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Control Theory & Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In this study, the authors address the problem of the mixed H2/H robust model predictive control (RMPC) for a class of discrete-time systems with structured uncertainty and disturbances. The conditions of RMPC are given to satisfy both the H2 and H performance requirements. In order to reduce the conservativeness caused by an unique feedback control law, a multi-step control strategy is introduced to improve the control performance and enlarge the feasible region of RMPC. Furthermore, an efficient version of the proposed RMPC is also given to reduce the online computational burden, which makes the design more practical. The proposed RMPCs are proven to be input-to-state practically stable (ISpS). A numerical example illustrates the effectiveness of the proposed designs.

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
      • L.H. Xie . Guaranteed cost control of uncertain discrete-time systems. Control Theory Adv. Technol. , 1235 - 1251
    7. 7)
      • Aliyu, M.D.S.: `Robust mixed ', Proc. American Control Conf., June 1999, San Diego, CA, p. 3367–3371.
    8. 8)
    9. 9)
      • Apkarian, P., Noll, D., Rondepierre, A.: `Mixed ', Proc. 48th IEEE Conf. on Decision and Control, 2009, p. 6460–6465.
    10. 10)
    11. 11)
    12. 12)
      • Orukpe, P.E., Imad, M.: `Model predictive control based on mixed control approach', Proc. 2007 American Control Conf., July 2007, New York City, USA, p. 11–13.
    13. 13)
    14. 14)
      • Orukpe, P.E., Jaimoukha, I.M.: `Robust model predictive control based on mixed ', Proc. European Control Conf., August 2009, Budapest, Hungary, p. 2223–2228.
    15. 15)
    16. 16)
    17. 17)
    18. 18)
    19. 19)
      • D.W. Li , Y.G. Xi . Design of robust model predictive control based on multistep control set. Acta Autom. Sin. , 4 , 433 - 443
    20. 20)
      • P. Gahinet , A. Nemirovski , A.J. Laub , M. Chilali . (1995) LMI control toolbox for use with matlab users guide.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2011.0187
Loading

Related content

content/journals/10.1049/iet-cta.2011.0187
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address