Transactions of the Korean Society of Automotive Engineers (한국자동차공학회논문집)

The Korean Society of Automotive Engineers (한국자동차공학회)
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A Study on the System Identification based on Neural Network for Modeling of 5.1. Engines

S.I. 엔진 모델링을 위한 신경회로망 기반의 시스템 식별에 관한 연구

  • Published : 2002.09.01
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Abstract

This study presents the process of the continuous-time system identification for unknown nonlinear systems. The Radial Basis Function(RBF) error filtering identification model is introduced at first. This identification scheme includes RBF network to approximate unknown function of nonlinear system which is structured by affine form. The neural network is trained by the adaptive law based on Lyapunov synthesis method. The identification scheme is applied to engine and the performance of RBF error filtering Identification model is verified by the simulation with a three-state engine model. The simulation results have revealed that the values of the estimated function show favorable agreement with the real values of the engine model. The introduced identification scheme can be effectively applied to model-based nonlinear control.

Keywords

References

  1. SAE 910083 Requirements and Performance of Engine Management System under Transient Conditions N.F.Benninger;G.Plapp
  2. 한국자동차공학회 논문집 v.7 no.7 제어기 설계를 위한 비선형 동적 엔진 모델링 선우명호;윤팔주
  3. SAE 961188 Model-based Fuel Injection System for SI Engines M.Nasu;A.Obata;S.Abe
  4. Trans. ASME, Journal of Dynamic Systems, Measurement and Control v.114 Modeling and Validation of Automotive Engines for Control Algorithm Development J.J.Moskwa;J.H.Hedrick
  5. SAE 910258 SI Engine Controls and Mean Value Engine Modeling E.Hendricks;S.C.Sorenson
  6. Neural Network Systems Techniques and Applications, In Control and Dynamic Systems v.7 C.T.Leondes
  7. Nonlinear Dynamical Control Systems H.Nijmeijer;A.J. Van der Schaft
  8. Adaptive Stabilization of Nonlinear Systems. In Foundation of Adaptive Control(P.V.Kokotovic, Ed.) L.Praly;G.Bastin;J.-B.Pomet;Z.P.Jiang
  9. Ph.D. Thesis Stable Adaptive Control and Recursive Identification of Nonlinear Systems Using Radial Gaussian Networks M.Sanner
  10. IEEE Trans. Neural Networks v.3 Gaussian Networks for Direct Adaptive Control M.Sanner;J.-J.E.Slotine
  11. IEEE Trans. Automat. Control AC v.11 Lyapunov Redesign of Model Reference Adaptive Control Systems C.Parks