• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.26-28
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• 2009

This paper proposes maximum torque control of IPMSM drive using adaptive teaming mechanism-fuzzy neural network (ALM-FNN) controller, model reference adaptive fuzzy tonal(MFC) and artificial neural network(ANN). This control method is applicable over the entire speed range which considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using ALM-FNN, MFC and ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN, MFC and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, MFC and ANN controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.321-326
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• 2006

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the copper and iron losses. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the hybrid artificial intelligent controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.416-419
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under-parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of loaming through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive loaming mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control(FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.504-510
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• 2015

Because wind generators (WGs) in a wind power plant (WPP) produce different active powers due to wake effects, the reactive power capability of each WG is different. This paper proposes a hierarchical voltage control scheme for a WPP that uses a WPP controller and WG controller. In the proposed scheme, the WPP controller determines a voltage error signal by using a PI controller and sends it to a doubly-fed induction generator (DFIG). Based on the reactive current-voltage ($I_Q-V$) characteristic of a DFIG, the DFIG injects an appropriate reactive power corresponding to the voltage error signal. To enhance the voltage recovery capability, the gains of the $I_Q-V$ characteristic of a DFIG are modified depending on its reactive current capability so that a DFIG with greater reactive current capability may inject more reactive power. The proposed scheme enables the WPP to recover the voltage at the point of common coupling (PCC) to the nominal value within a short time after a disturbance by using the adaptive $I_Q-V$ characteristics of a DFIG. The performance of the proposed scheme was investigated for a 100 MW WPP consisting of 20 units of 5 MW DFIGs for small and larger disturbances. The results show the proposed scheme successfully recovers the PCC voltage within a short time after a disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.457-462
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• 2005

Industrial and economical importance of CP(Cellular Phone) is growing rapidly. Combined with IT technology, CP is currently one of the most attractive technologies for all. However, unless we find a breakthrough to the technology, its growth may slow down soon. RT(Robot Technology) is considered one of the most promising next generation technology. Unlike the industrial robot of the past, today's robots require advanced technologies, such as soft computing, human-friendly interface, interaction technique, speech recognition, object recognition, and many others. In this study, we present a new technological concept named RCP(Robotic Cellular Phone), which combines RT & CP, in the vision of opening a new direction to the advance of CP, IT, and RT all together. RCP consists of 3 sub-modules. They are $RCP^{Mobility}$, $RCP^{Interaction}$, and $RCP^{Interaction}$. $RCP^{Mobility}$ is the main focus of this paper. It is an autonomous navigation system that combines RT mobility with CP. Through $RCP^{Mobility}$, we should be able to provide CP with robotic functionalities such as auto-charging and real-world robotic entertainments. Eventually, CP may become a robotic pet to the human being. $RCP^{Mobility}$ consists of various controllers. Two of the main controllers are trajectory controller and self-localization controller. While Trajectory Controller is responsible for the wheel-based navigation of RCP, Self-Localization Controller provides localization information of the moving RCP. With the coordinate information acquired from RFID-based self-localization controller, Trajectory Controller refines RCP's movement to achieve better RCP navigations. In this paper, a prototype system we developed for $RCP^{Mobility}$ is presented. We describe overall structure of the system and provide experimental results of the RCP navigation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.73-82
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• 2022

Driver acceptance of autonomous driving is very important. The autonomous driving longitudinal controller, which is one of the factors affecting acceptability, consists of a high-level controller and a low-level controller. The host controller decides the cruise control and the space control according to the situation and creates the required target speed. The sub-controller performs control by creating an acceleration signal to follow the target speed. In this paper, we propose an algorithm to improve the inter-vehicle distance fluctuations that occur in the cruise control and space control switching problems in the host controller. The proposed method is to add an approach algorithm to the cruise control at the time of switching from cruise control to space control so that it is switched to space control at the correct switching distance. Through this, the error was improved from 12m error to 4m, and actual vehicle verification was performed.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.32-35
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• 1997

A recent development in the Flat Panel Display(FPD) industry requires an auto-alignment system which is operated in high speed and high precision. In the FPD production process, aligning photo-mask with respect to guide mark printed in the glass should be accomplished in the accuracy of sub-micron order. So the system has high bandwidth and needs a dedicated control system which is fast and robust enough to control linear motors in precise manner. Proposed auto-alignment system structure in this presentation which consists of the master controller board, the DSP position controller board which controls 3 axis precision linear motors, the servo system and the man machine interface software. Designed and tuned under repeated experiments, the proposed system showed a reasonable performance in the aspect of rise time and steady state error.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1207-1210
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• 2003

In this paper, studied traveling by ummaned vehicles using MPC sensor.Explain what is MPC sensor and also is threaded how on vehicles. Made use of PID controller and LQG/LTR controller that is used much in present industrial circles for control of this.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.319-322
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• 1995

This paper addresses that through the use of Fuzzy Logic Control, a reactiv behavior (e.g. avoiding obstacles on the way) are smoothly blended into one sequence of control action. In this classical problem, the aim is to guide a mobile robot along its path to avoid any static obstacles in front of it. This controller presented here uses three sub-controllers. This fuzzy controller was apply to a miniature mobile robot. This robot follows a left wall, maintining a minimum distance.

• Proceedings of the KIEE Conference
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• 2007.10c
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• pp.126-128
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• 2007

This paper proposes maximum torque control of IPMSM drive using Adaptive Fuzzy-Neuro controller and artificial neural network(ANN). The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. This paper proposes the analysis results to verify the effectiveness of the Adaptive Fuzzy-Neuro and ANN controller.