• Journal of the Korean Society for Precision Engineering
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• v.26 no.9
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• pp.14-22
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• 2009

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.5
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• pp.115-121
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• 2001

A driving load estimation method for intelligent cruise control(ICC) vehicles has been proposed in this paper. Vehicle driving load is one of the most important factors of perturbations in vehicle control and can affect the control performance critically. The effect of the control with driving load estimation on vehicle-to-vehicle distance control has been presented and investigated via computer simulations and vehicle tests. The results show that vehicle-driving-load-adaptive control can provide an ICC system with a good acceleration tracking performance. In addition, the results show that driving load estimation can compensate not only the variation of driving load but also the modeling errors.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.286-295
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• 2007

This paper presents an intelligent PID control for stochastic systems with nonstationary nature. We optimally determine parameters of a PID controller through learning algorithm and propose an online PID control to compensate system errors possibly occurred in realtime implementations. A dynamic Bayesian network (DBN) model for system errors is additionally explored for making decision about whether an online control is carried out or not in practice. We apply our control approach to traffic control of Transmission Control Protocol (TCP) networks and demonstrate its superior performance comparing to a fixed PID from computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.302-305
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• 1999

Twin-servo mechanism is used to increase the payload capacity and speed of high precision motion control system. In this paper, we propose a robust synchronizing motion control algorithm to cancel out the skew motion of twin-servo system caused by different dynamic characteristics of two driving systems and the vibration generated by high accelerating and decelerating motions. This proposed control algorithm consists of separate feedback motion control algorithm of each driving system and skew motion compensation algorithm between two systems. Robust model reference tracking controller is proposed as a separate motion controller and its disturbance attenuation property is shown. For the synchronizing motion, skew motion compensation algorithm is designed, and the stability of whole Closed loop system is proved based on passivity theory.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.653-658
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• 2000

A driving load estimation method for intelligent cruise control(ICC) vehicles has been proposed in this paper. The driving load is one of the most important factors of perturbations in vehicle control and can affect the control performance critically. The Effect of the control with driving load estimation on vehicle-to-vehicle distance control has been presented and investigated via computer simulations and vehicle tests. The results show that the control with driving load estimation can provide ICC system with a good acceleration tracking performance. In addition, the results show that driving load estimation can compensate not only variation of driving load but also the modeling errors.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.984-988
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• 2005

To accomplish various and complex tasks by intelligent robots, improvement is needed not only in mechanical system architecture but also in control system architecture. Hybrid control architecture has been suggested as a mutually complementing architecture of the weak points of a deliberative and a reactive control. This paper addresses a control architecture of robots, and a behavior representation methodology. The suggested control architecture consists of three layers of deliberative, sequencing, and reactive as hybrid control architecture. Multi-layer behavior model is employed to represent desired tasks. 3D simulation will be conducted to verify the applicability of suggested control architecture and behavior representation method.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.5
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• pp.303-309
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• 2011

In this paper, an intelligent force control technique is applied to an autonomous helicopter. Although most research on the autonomous helicopter system is about navigation and control, force control of an autonomous helicopter system is quite new and not presented yet. After controlling the position of the helicopter by the LQR method, force control is applied. The adaptive impedance force control algorithm is introduced and tested to regulate the desired force under unknown location and stiffness of the environment. To compensate for uncertainty from outer disturbance, a neural network is added to form an intelligent force control framework. Simulation studies show that the proposed force control algorithm works well.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.1
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• pp.5-11
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• 2002

Active vibration control of intelligent laminated composite plates is performed experimental1y Laminated composite place is modeled by the system identification method. For the system identification process, the laminated composite place is excited by two piezoelectric actuators with PRBS signals. At the same time, the displacement of the laminated composite plate is measured by a gap sensor. From these excited PRBS signals and the measured displacement sequence, system parameters of the laminated composite plate are estimated using a recursive prediction error method. Model of the laminated composite plate with two piezoeletric actuators is assumed to be the form of ARMAX. From the estimated ARHMAX model, a state space equation of the observable canonical form is obtained. With this state space equation, a controller and an observer for active vibration control is designed using the optimal control method. Controller and observer are implemented on a digital system. Experiments on the vibration control are Performed with changing the outer layer fiber orientation of intelligent composite plates.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.479-486
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• 2013

There exist two major difficulties in developing flight control system: nonlinear dynamic characteristics and time-varying properties of parameters of aircraft. Instead of the difficulties, many high reliable and efficient control methodologies have been developed. But, most of the developed control systems are based on the exact mathematical modelling of aircraft and, in the absence of such a model, it is very difficult to derive performance, robustness and nominal stability. From these aspects, recently, some approaches to utilizing the intelligent control theories such as fuzzy logic control, neural network and genetic algorithm have appeared. In this paper, one advanced intelligent lateral control system of a high speed fight has been developed utilizing type-2 fuzzy logic, which can deduce the uncertainty problem of the conventional fuzzy logic. The results will be verified through computer simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.454-457
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• 2004

In this paper, control method proposed for effective speed control of the induction motor indirect vector control. For the induction motor drive, indirect vector control scheme that controls torque current and flux current of the stator current independently so that it can have improved dynamics. Also, neuro-fuzzy algorithm employed for torque current control in order to optimal speed control The proposed neuro-fuzzy algorithm can be applied to the precise speed control of an induction motor drive system or the field of any other power systems.