• Journal of Mechanical Science and Technology
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• v.19 no.10
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• pp.1846-1855
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• 2005

This paper presents a new stochastic controller applied on the vibration control system under irregular disturbances based on the mode selection scheme. Measured displacement and frequency characteristics are simultaneously used in designing a mode selecting controller. This technique is validated by applying to the suppression problem of a flexible beam with randomly vibrated circumstances. The presented method, called Mode Selecting Stochastic Controller, uses the frequency measurement of the flexible system based on a Fast-Fourier transformation algorithm. This controller is constructed by combining mode selection method with previous known Stochastic Controller in real time: Numerical simulations and several experiments are conducted to validate the proposed method. The performance of the proposed method is compared with a stochastic controller developed recently. This method was improved compared with previous one.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.715-718
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• 2002

A control strategy for a dynamic system under Irregular disturbance by using stochastic controller is developed. In order to design stochastic controller. system dynamic model in real domain is transformed dynamic moment equation in stochastic domain by F-P-K approach. A study of real time control technique for stochastic controller is presented. The performance of stochastic controller is verified through experiment used by real time control technique method.

• Journal of KSNVE
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• v.9 no.3
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• pp.502-508
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• 1999

Newly developed control methodology applied to dynamic system under random disturbance is investigated and its performance is verified experimentall. Flexible cantilever beam sticked with piezofilm sensor and piezoceramic actuator is modelled in physical domain. Dynamic moment equation for the system is derived via Ito's stochastic differential equation and F-P-K equation. Also system's characteristics in stochastic domain is analyzed simultaneously. LQG controller is designed and used in physical and stochastic domain as wall. It is shown experimentally that randomly excited beam on the base is controlled effectively by designed LQG controller in physical domain. By comparing the result with that of LQG controller designed in stochastic domain, it is shown that new control method, what we called $\ulcorner$Heo-stochastic controller design technique$\lrcorner$, has better performance than conventional ones as a controller.

• Journal of Mechanical Science and Technology
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• v.20 no.5
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• pp.652-657
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• 2006

Although many methods about the control of irregular external noise have been introduced and implemented, it is still necessary to design a controller that will be more effective and efficient methods to exclude for various noises. Accumulation of errors due to model tracking, internal noises (thermal noise, shot noise and 1/f noise) that come from elements such as resistor, diode and transistor etc. in the circuit system and numerical errors due to digital process often destabilize the system and reduce the system performance. New stochastic controller is adopted to remove those noises using conventional controller simultaneously. Design method of a model tracking dual controller is proposed to improve the stability of system while removing external and internal noises. In the study, design process of the model tracking dual stochastic controller is introduced that improves system performance and guarantees robustness under irregular internal noises which can be created internally. The model tracking dual stochastic controller utilizing F-P-K stochastic control technique developed earlier is implemented to reveal its performance via simulation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.525-528
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• 2005

Much of the study has been dong on the design of dual controller that guarantee the stability and improvement of the system performance. A dual controller concept is proposed to consist of first controller estimates the control law and second controller suppresses the combined noises due to numerical error and internal noise as well. These irregular disturbances are not only increasing the fatigue but also destabilize the system because of unwanted output performance. The 'stochastic controller' is used to suppress the irregular random disturbance. Simulation is conducted to reveal that the proposed dual stochastic controller is highly efficient one to control a system hybrid noises.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.6 s.99
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• pp.757-763
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• 2005

Much of the study has been done on the design of dual controller that guarantee the stability and improvement of the system performance. A dual controller concept is proposed to consist of first controller estimates the control law and second controller suppresses the combined noises due to numerical error and internal noise as well. These Irregular disturbances are not only increasing the fatigue but also destabilize the system because of unwanted output Performance. The 'stochastic controller' is used to suppress the irregular random disturbance. Simulation is conducted to reveal that the proposed dual stochastic controller is highly efficient one to control a system hybrid noises.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.263-272
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• 2000

In this paper we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastcic approximation method it is regarded as a stochastic recursive filter algorithm. In addition we provide a filtering and control condition for a stochastic nonlinear system called the perfect filtering condition in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable and the proposed neural controller is more efficient than the conventional LQG controller and the canonical LQ-Neural controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.346-352
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• 1998

In this paper, we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastic approximation method, it is regarded as a stochastic recursive filter algorithm. In addition, we provide a filtering and control condition for a stochastic nonlinear system, called perfect filtering condition, in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence, the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable. and the proposed neural controller is more efficient than the conventional LQG controller and the canoni al LQ-Neural controller.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.1054-1057
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• 2003

A Real Time Mode Selecting Stochastic Controller (RTMSSC) is developed as a new control strategy for a vibrating system under irregular disturbance. Displacement information and frequency characteristics obtained from me::id analysis of the system are used to design a Mode Selecting Controller. This Paper explains design technique of RTNSSC by applying it to the suppression of a flexible beam experiencing random vibration. The RTMSSC is designed by stochastic control from the modal information. The frequency information of the flexible system is utilized from the Mode Selecting Unit (MSU) based on a Fast-Fourier Transformation algorithm. The performance of the proposed technique, RTMSSC, is compared with that of Real Time Stochastic Controller developed recently, which show quite promising results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.215-218
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• 2002

A control strategy for a dynamic system under irregular disturbance by using stochastic controller is developed. In order to design stochastic controller, system dynamic model in real domain i transformed dynamic moment equation in stochastic domain by F-P-K approach. A study of real time control technique four stochastic controller is performed in this paper.