한국정밀공학회지 (Journal of the Korean Society for Precision Engineering)
- 제14권7호
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- Pages.29-38
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- 1997
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- 1225-9071(pISSN)
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- 2287-8769(eISSN)
신경회로망을 응용한 현가장치의 폐회로 시스템 규명
Empirical Closed Loop Modeling of a Suspension System Using Neural Network
- Kim, I.Y. (Dept.of Control Instrumentation Engineering, Engineering College, Chonbuk National University) ;
- Chong, K.T. ;
- Hong, D.P.
- 발행 : 1997.07.01
초록
A closed-loop system modeling of an active/semiactive suspension system has been accomplished through an artificial neural network. A 7DOF full model as a system's equation of motion has been derived and an output feedback linear quadratic regulator has been designed for control purpose. A training set of a sample data has been obtained through a computer simulation. A 7DOF full model with LQR controller simulated under several road conditions such as sinusoidal bumps and rectangular bumps. A general multilayer perceptron neural network is used for dynamic modeling and target outputs are fedback to the a layer. A backpropagation method is used as a training algorithm. Model validation of new dataset have been shown through computer simulations.