• Title/Summary/Keyword: Full State Feedback Controller(FSFC)

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Stabilization of Ball-Beam System using RVEGA SMC (RVEGA SMC를 이용한 Ball-Beam 시스템의 안정화)

  • Kim, Tae-Woo;Lee, Joon-Tark
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.10
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    • pp.1327-1334
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    • 1999
  • The stabilization control of ball-beam system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of classical methods such as the PID and the full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Therefore, in this paper, three improved design techniques of stabilization controller for a ball-beam system were proposed. These parameter tuning methods in the double PID controller(DPIDC), the FSFC and the a sliding mode controller(SMC) were dependent upon the Real Value Elitist Genetic Algorithm (RVEGA). Finally, by applying the DPIDC, the FSFC and the Real Variable Elitist Genetic Algorithm based Sliding Mode Control(RVEGA SMC) to the stabilizations of a ball-beam system, the performances of the RVEGA SMC technique were showed to be superior to those of two other type controllers.

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A Study on the Stabilization Control of Nonlinear Systems using RVEGA SMC (RVEGA SMC를 이용한 비선형 시스템의 안정화 제어)

  • Kim, Tae-Woo;Jo, Hyun-Woo;Song, Ho-Shin;Lee, Oh-Keol;Lee, Joon-Tark
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.2624-2626
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    • 2000
  • The stabilization controls of coupled tank system and ball-beam system are difficult control tasks because of their high order time delay, nonlinearity and structural unstability. Fuhermore, a series of classical methods such as a conventional PID and a full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. Therefore, in this paper, in order to stabilize two representative nonlinear system mentioned above, a Sliding Mode Controller based on a Real Variable Elitist Genetic Algorithm(RVEGA SMC) was proposed.

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