제어로봇시스템학회:학술대회논문집
- 제어로봇시스템학회 2001년도 ICCAS
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- Pages.41.4-41
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- 2001
LQR Controller Design for Active Suspensions using Evolution Strategy and Neural Network
- Cheon, Jong-Min (Korea Electrotechnology Research Institute) ;
- Park, Young-Kiu (Pusan Univ.) ;
- Kim, Sungshin (Pusan Univ.) ;
- Kim, Dae-Jun (Pusan Univ.) ;
- Lee, Min-Jung (Pusan Univ.)
- 발행 : 2001.10.01
초록
In this paper, we propose a LQR(Linear Quadratic Regulator) controller design for the active suspension using two-degree-of-freedom quarter-car model. We can improve the inherent suspension problem, the tradeoff between ride quality and suspension travel by selecting appropriate weights in the LQR-objective function. Because any definite rules for selecting weights do not exist, we replace the designer´s trial and error with the optimization-algorithm, ES(Evolution Strategy). Using the ES, we can find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle´s state variables.
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