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Integrated Guidance and Control Design Based on Adaptive Neural Network for Unpowered Air Vehicle

  • 김부민 (경상대학교 기계항공공학부) ;
  • 성덕용 (국방과학연구소) ;
  • 성재민 (경상대학교 기계항공공학부) ;
  • 김병수 (경상대학교 기계항공공학부)
  • 발행 : 2009.01.01


The guidance controller of the conventional aircraft consists of inner-loop (autopilot) and outer-loop (guidance). If the guidance controller can be designed as an integrated guidance and control (IGC), the various advantages exist. The integrated guidance and control formulation can compensate for the effect of autopilot lag. An integrated approach also helps avoid the iterative procedure involved in tuning the guidance and autopilot subsystems, if designed separately. Integrated design is also less susceptible to saturation and stability problems. This paper presents an approach to IGC design for the unpowered air vehicle with the only flaperon using a combination of adaptive output feedback inversion and backstepping techniques. Adaptive neural networks are trained online with available measurements to compensate for unmodeled nonlinearities in the design process.


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