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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2000, Vol. 21 ›› Issue (1): 84-86.

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NEURAL NETWORKS BASED ADAPTIVE FEEDBACK LINEARIZATION FOR BANK-TO-TURN MISSILE CONTROL

ZHANG Youan, YANG Xu, CUI Pingyuan, YANG Di   

  1. P.O.Box 137, Harbin Institute of Technology , Harbin 150001, China
  • Received:1998-10-12 Revised:1999-06-02 Online:2000-02-25 Published:2000-02-25

Abstract:

Based on the theory of feedback linearization and the simplified bank to turn (BTT) control design model, a BTT missile autopilot design method is presented. No zero dynamics exists in the proposed scheme. A method for generating an attack command from the normal over load command is presented. Based on this, the CMAC neural networks are introduced for adaptive feedback linearization of bank to turn missiles, and hence the desired tracking performance of the practical missile system with uncertainty is achieved. A stability proof is given strictly in the sense of Lyapunov. The proposed scheme is fit for the entire flight envelope of the BTT missile. Simulation results have shown the rightness and effectiveness of the proposed scheme.

Key words: autopilot, bank-to-turn missile, feedback linearization, CMAC neural networks, adaptive control

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