DOI QR코드

DOI QR Code

무추력 비행체를 대상으로 한 적응 통합 유도제어기 설계

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

초록

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.

참고문헌

  1. E. Johnson and S.K.annan, "Adaptive Flight Controlforan Autonomous Unmanned Helicopter," AlAA Guidance, Navigation, and Control Corrference, Monterey, CA, Aug. 2002
  2. P. K. Menon and E. J. Ohlmeyer, "Integrated Designof Agile Missile Guidance and Autopilot Systems," IFAC-Control Engineering Practice, vol. 9, pp. 1095-1106, 2001
  3. P. K. Menon, G D. Sweriduk, and E. J. Ohlmeyer, "OptimalFixed-Interval Integrated Guidance-Control Laws for Hit-to-Kill Missiles," AlAA Guidance, Navigation, and Control Conference, Austin, TX, Aug. 2003
  4. N. F. Palumbo and T. D. Jackson, "Integrated Missile Guidance and Control: A State Dependent Riccati Differential EquationApproach," IEEE International Conference on Control Applications, vol. 1, pp. 243-248, Aug. 1999
  5. N. Hovakimyan, A. J. Calise, and N. Kim, "Adaptive Output Feedback Control of a Class of Multi-Input Multi-OutputSystemsusingNeuralNetworks," International Journal of Control, vol. 77, no. 15, pp 1318-1329, Oct. 2004
  6. M. ldan, A. J. Calise, and N. Hovakimyan., "An AdaptiveOutput Feedback Control Methodology: Theory and PracticalImplementation Aspects," AlAA Guidance, Navigation, and Control Conference and Exhibit, Monterey, California, Aug.2002
  7. M. Sharma and N. Richards, "Adaptive, Integrated Guidance and Control for Missile Interceptors," AlAA Guidance, Navigation, and Control Conference, Providence, RI, Aug. 2004
  8. M. Krstic, I. Kanellakopoulos, and P. Kokotovic, Nonlinear and Adaptive Control Design, John Wiley & Sons, Inc., New York,1995
  9. B. S. Kim, A. J. Calise, and R J. Sattigeri, "Adaptive, Integrated, Guidance and Control Design for Line-of-Sight based Formation Flight," Journal of Guidance, Control, and Dynamics,vol. 30, no. 5, pp. 1386-1398, Sep.2007
  10. B. S. Kim and A. J. Calise, "Nonlinear Flight Control Using Neural Networks," AlAA Journal of Guidance, Control, and pynamics, vol. 20, no. 1,1997
  11. Ramachandra Dattigeri, "Adaptive Estimation and Control withApplication to Vision-Based Autonomous Formation Flight,"Degree Doctor, Georgia Institute of Technology, Aug. 2007
  12. S. J. Lee, J. H. Cho, S. W. Lee, and J. S. Cho, ''N\llllerical Study on the Aerodynamic Characteristics ofWmgs on the FormationFlight," Journal of The Korean Society for Aeronautical and Space Sciences, vol. 35, no. 1, pp. 18-26,2001