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Anti-input windup dynamic neural networks control for flexible hypersonic vehicles

ZHAO Hewei, LIANG Yong, YANG Xiuxia   

  1. Department of Control Engineering, Naval Aeronautical and Astronantical University, Yantai 264001, China
  • Online:2017-03-23 Published:2010-01-03

Abstract:

The dynamic process of the flexibility mode is analyzed and the controller is designed based on the inner loop and outer loop systems for the flexible hypersonic vehicle. Considering the angle of attack and the pitch rate as the states of the inner loop systems and the elevator deflection as the control input, the controller is designed by the backstepping method, the question of control input windup is solved with the anti-input windup supplementary systems in case of considering the dynamic process of the flexibility mode. The windup character of control input is approximated by fully tuned dynamic neural networks. Considering the flight speed as the states of outer loop systems and the equivalence ratio as the control input, the controller is designed based on the terminal sliding mode control method. The question of control input windup is solved with the anti-input windup supplementary systems and assuring the favorable dynamic character of flexibility mode, the input windup character is approximated by the fully tuned dynamic neural networks. Based on the stability theorem, all the signals of the systems are bounded and exponentially converge to the neighborhood of the origin globally. The simulation results demonstrate that order signals can be traced effectively by states of the system and the dynamic character of the flexibility mode is favorable.

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