Adaptive decoupling control of hypersonic vehicle using fuzzy-neural network observer

An adaptive decoupling control approach using fuzzy-neural network (FNN) observer for a class of MIMO nonlinear systems with parameter uncertainties is presented in this article. First, a decoupling controller is constructed based on the decentralized control theory. Furthermore, the system coupling terms and uncertainties are estimated by the FNN observer and added into the control law for compensation. The FNN approximate-matrix update law and the control law guarantee that the tracking errors of the system states, the observer states and the approximate matrix are all uniformly ultimately bounded within a region that can be kept arbitrarily small. Secondly, a model for the hypersonic vehicle is given and an attitude controller is designed using the decoupling control approach. Finally, simulations are carried out on the hypersonic vehicle to demonstrate the effectiveness of the proposed method.

• Record URL:
  • https://doi.org/10.1177/0954410015606165
• Record URL:
  • http://pig.sagepub.com/cgi/content/abstract/230/7/1216
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/19966973
• Supplemental Notes:
  • Reprinted by permission of Sage Publications, Ltd.
• Authors:
  • Bai, Chen
  • Chen, Jian
  • Ren, Zhang
  • Li, Qingdong
  • Xiong, Zihao
• Publication Date: 2016-6

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 1216-1223
• Serial:
  • Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
  • Volume: 230
  • Issue Number: 7
  • Publisher: Sage Publications, Incorporated
  • ISSN: 0954-4100
  • EISSN: 2041-3025
  • Serial URL: http://pig.sagepub.com/

Subject/Index Terms

• TRT Terms: Adaptive control; Fuzzy logic; Hypersonic aircraft; Neural networks
• Uncontrolled Terms: Decoupling
• Subject Areas: Aviation; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01600820
• Record Type: Publication
• Files: TRIS
• Created Date: May 31 2016 9:17AM