Journal of Astronautics ›› 2011, Vol. 32 ›› Issue (5): 1039-1046.doi: 10.3873/j.issn.1000-1328.2011.05.012

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Adaptive Trajectory Linearized Control for Maneuvering Reentry Vehicle

LI Hai   

  1. 1. No.803 Research Institude of Shanghai Academy of Spaceflight Technology, Shanghai 200233, China;
    2. Center for Control Theory and Guidance Technology, Harbin Institute of Technology, Harbin
    150001,China
  • Received:2010-04-26 Revised:2010-06-15 Online:2011-05-15 Published:2011-06-14

Abstract: An adaptive trajectory linearized control method (ATLC) based on generalized fuzzy neural network
(G\|FNN) is proposed for a kind of multi\|input/multi\|output system with nonlinear model uncertainties. The ATLC controller is designed and analyzed for the six\|Dof nonlinear dynamics of a maneuvering reentry vehicle (MRV). The aerodynamic parameter uncertainties of MRV can become large and result in poor robustness of the standard TLC controller. The G\|FNN is introduced to approximate model nonlinear uncertainties adaptively, thus improving the controller performance. The stability of the closed\|loop control system is proved by using the Lyapunov stability theory. Simulation studies demonstrate that the ATLC controller is robust with respect to large parametric uncertainties.

Key words: Adaptive control, Fuzzy neural networks, Trajectory linearization control, Reentry vehicle

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