• Proceedings of the KSME Conference
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• 2000.04a
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• pp.458-463
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• 2000

This paper presents a design of the controller for vehicle lateral dynamics using active yaw moment. Vehicle lateral motion is incorporated with directional controllability and stability. These are conflicting each other from the view of vehicle handling performance. To compromise the trade-off between these two aspects, we suggest a new control algorithm based on the sliding mode with time-varying switching surface according to the body side slip angle. The controller can deal with the nonlinear region in vehicle driving and be robust to the parameter uncertainties in the plant model. Control performance was evaluated from the simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.777-786
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• 1999

This work is concerned with the assignment of the desired eigenstructure for linear time-varying systems such as missiles, rockets, fighters, etc. Despite its well-known limitations, gain scheduling control appeared to be the focus of the research efforts. Scheduling of frozen-time, frozen-state controller for fast time-varying dynamics is known to be mathematically fallacious, and practically hazardous. Therefore, recent research efforts are being directed towards applying time-varying controllers. In this paper, ⅰ) we introduce a differential algebraic eigenvalue theory for linear time-varying systems, and ⅱ) we also propose an eigenstructure assignment scheme for linear time-varying systems via the differential Sylvester equation based upon the newly developed notions. The whole design procedure of the proposed eigenstructure assignment scheme is very systematic, and the scheme could be used to determine the stability of linear time-varying systems easily as well as provides a new horizon of designing controllers for the linear time-varying systems. The presented method is illustrated by a numerical example.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.225-225
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• 2000

We propose the hybrid robust controller for TDC(Time Delay Control) and SMC(Sliding Mode Control) method. TDC and SMC deal with the time-varying system parameters, unknown dynamics and unexpected disturbance. This controller is applied to follow the desired reference model for the uncertain time-varying overhead crane. The control performance is evaluated through simulation. The theoretical results indicate That the proposed controller shows excellent performance to an overhead crane with the uncertain time-varying parameters and disturbance.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.286-286
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.154-161
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.666-672
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• 2003

This paper presents a design of the controller for vehicle lateral dynamics using active yaw moment. Vehicle lateral motion is incorporated with directional controllability and stability. These are conflicting each other from the view of vehicle handling performance. To compromise the trade-off between these two aspects, we suggest a new control algorithm based on the sliding mode with time-varying switching surface according to the body side slip angle. The controller can deal with the nonlinear region in vehicle driving condition and be robust to the parameter uncertainties in the plant model. Control performance is evaluated from the simulation for the vehicle of real parameters on the road with various tire-road frictions.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.61.2-61
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• 2002

$\textbullet$ Introduction $\textbullet$ Dynamics of robotic manipulator $\textbullet$ Time-varying sliding surface $\textbullet$ Fuzzy rule, Membership function $\textbullet$ Application to a two degree robotic manipulator $\textbullet$ Conclusion

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.210-219
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• 2010

Consumers differ in both horizontally and vertically. Market segmentation aims to divide horizontally different (or heterogeneous) consumers into more similar (or homogeneous) small segments. A specific consumer, however, may differ in vertically. He (or she) may belong to a different market segment from another one where he (or she) belonged to before. In consumer panel data, the vertical difference can be observed by his (or her) choice among brand alternatives are changing over time. The consumer's vertical difference has been defined as 'dynamics'. In this research, we have developed a binary probit model with random-walk coefficients to capture the consumer's dynamics. With an application to a consumer panel data, we have examined how have the random-walk coefficients changed over time.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.758-767
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• 2000

The properties of linear time-varying(LTV) systems vary because of the time-varying property of plant parameters. The generalized controller design method for linear time-varying systems does not exit because the analytic soultion of dynamic equation has not been found yet. Hence, to design a controller for LTV systems, the robust control methods for uncertain LTI systems which are the approximation of LTV systems have been generally ised omstead. However, these methods are not sufficient to reflect the fast dynamics of the original time-varying systems such as missiles and supersonic aircraft. In general, both the performance and the robustness of the control system which is designed with these are not satisfactory. In addition, since a better model will give the more robustness to the controlled system, a gain scheduling technique based on LTI controller design methods has been uesd to solve time problem. Therefore, we propose a new gain scheduled QFT method for LTV systems based on neural networks in this paper. The gain scheduled QFT involves gain dcheduling procedured which are the first trial for QFT and are well suited consideration of the properties of the existing QFT method. The proposed method is illustrated by a numerical example.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.27-31
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• 2001

In this paper, we consider the guaranteed cost filtering design method for time-varying delay system with parameter uncertainties by LMI(Linear Matrix Inequality) approach. The objective is to design a stable guaranteed cost filter which minimizes the guaranteed cost fo the closed loop systems in filtering error dynamics. The sufficient conditions for the existence of filter, the guaranteed cost filter design method, and th guaranteed cost upper bound are proposed by LMI technique in terms of all finding variables. Finally, we give an example to check the validity of the proposed method.