• 한국항만학회지
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• 제14권3호
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• pp.291-301
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• 2000

T his paper presents the lateral and longitudinal control algorithm for the driving of a 4WS AGV(Automated Guided Vehicle). The control law to the lateral and longitudinal control of the AGV includes adaptive agin tuning ability, that is the controller gain of the gravity compensated PD controller can be changed on a real-time. The gain tuning law is derived from the Lyapunov direct method using the output error of the reference model and the actual model, And to show the performance of the presented lateral and longitudinal control algorithm, we simulate toe nonlinear AGV equations of the motion by deriving the Newton-Euler Method, The read path is from quay yard area to docking position in loading yard area. The quay yard area is where the quay crane loads the container to the AGV and the docking position is where the container is transferred to the gantry crane. The road types are constructed in a straight line and J-turn. When driving the straight line, the driving velocity is 6㎧ and the J-turn is 3㎧.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제51권3호
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• pp.150-157
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• 2002

This paper presents preliminarily an implementation of digital high-performance motion control system of Reluctance Synchronous Motor (RSM) drives with direct torque control (DTC). The system consist of stator flux observer, torque estimator, two hysteresis band controllers, an optimal switching look-up table, IGBT voltage source inverter, and TMS320F240 DSP controller made by Texas Instruments. The stator fluff observer is based on the combined voltage and current model with stator flux feedback adaptive control, and the input of the observer are the stator voltage and current of motor terminal for wide speed range. The rotor position and speed sensor used 6000 pulse/rev encoder. In order to prove rightness of the suggested control algorithm, we have some simulation and actual experimental system at $\pm$20 and $\pm$2000 rpm. The developed digitally high-performance motion control system+ are shown a good response characteristic of control results and high performance features using 1.0kW RSM which has 2.57 Ld/Lq salient ratio.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제49권10호
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• pp.693-700
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• 2000

A direct torque control algorithm for 3-level inverter-fed induction motors is presented. Conventional voltage selection methods provoke some problems such as stator flux drooping phenomenon and undersirable torque control appeared especially at the low speed operation. To overcome these problems, a proposed method uses intermediate voltage vectors, which are inherently generated in 3-level inverters. In the proposed algorithm, both subdivision of the basic switching sectors and applications of tntermediated voltages improve the low speed operation characteristics. This algorithm basically considers applications in which direct torque controlled induction motors are fed by 3-level inverters with low switching frequency around 500Hz. An adaptive observer is also employed to bring better responses at the low speed operation, by estimating some state-variables, motor speed and motor parameters which take a deep effect on the performance of the low speed operation. Simulation and experiment results verify effectiveness of the proposed algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.898-901
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• 1988

Up to now, using adaptive control method, Identification deals with system whose entire state variables and prameters are accessible for measurement. In practical situations, all the state variables cannot be measured and it is impossible to directly apply since the parameters of the system are unknown. Therefore, in this paper, using only input-output data, such a model of the system is not available since the parameters of the system are unknown. this leads to the concept of an adptive observer in which both the parameters and the state variable of the system are identified simultaniously. Lyapunov's direct method and Kalman-Yakubovich (K-Y) lemma are employed to ensure the stability of this schemes. The feature is that the signal and adaptive gain which is generated from filter is imposed upon feedback vector and then state variables and the unknown parameters can be identified. To show the usefulness of the proposed schemes, computer simulation result of unknown second-order system shows the effectiveness of the proposed schems.

• 대한임베디드공학회논문지
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• 제13권2호
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• pp.83-91
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• 2018

With the development of IT (Information Technology) technology, embedded system and network technology are combined and used in various environments such as military environment as well as everyday life. In this paper, we propose a new airdropped distributed mobility model (ADMM) modeling the dispersion falling of the direct shot of a cluster bomb, and we compare and analyze some representative MANET routing protocols in ADMM in ns-3 simulator. As a result of the analysis, we show OLSR routing protocol is promising in ADMM environment in the view points of packet delivery ratio (PDR), end to end delay, and jitter. In addition, we propose a new adaptation scheme for OLSR, AND-OLSR (Average Node Distance based adaptive-OLSR) to improve the original OLSR in ADMM environment. The new protocol calculates the average node distance, adapts the period of the control message based on the average node distance increasing rate. Through the simulation study, we show that the proposed AND-OLSR outperforms the original OLSR in PDR and control message overhead.

• Journal of Power Electronics
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• 제14권1호
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• pp.125-134
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• 2014

This paper presents a robust and speed-sensorless stator flux estimation for induction motor direct torque control. The proposed observer is based on sliding mode approach. Stator electrical equations are used in the rotor orientation reference frame to eliminate the observer dependence on rotor speed. Lyapunov's concept for systems stability is adopted to confine the observer gain. Furthermore, the sensitivity of the observer to parameter mismatch is recovered with an adaptation technique. The nonlinearities of the pulse width modulation voltage source inverter are estimated and compensated to enhance stability at low speeds. Therefore, a new method based on the model reference adaptive system is proposed. Simulation and experimental results are shown to verify the feasibility and effectiveness of the proposed algorithms.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 A
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• pp.574-577
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• 1996

In order to reduce the torque pulsation caused by non-sinusoidal flux distribution of the brushless direct drive motor(BLDDM), a new torque control technique is proposed. The linkage flux of the BLDDM is first estimated by using the model reference adaptive system (MRAS) technique and the instantaneous torque of the BLDDM is then estimated from the mathematical model including this estimated linkage flux. By using the estimated instantaneous torque of the BLDDM, the minor torque control loop to suppress the undesirable torque pulsation is designed. To show the effectiveness of the proposed control scheme, the simulations and experiments are carried out for the DSP-based BLDDM drive system with a power rate of 120W. It is well demonstrated from these results that the torque and speed control performance of the BLDDM is much improved by employing the proposed control scheme.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 B
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• pp.986-988
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• 2001

This paper presents a digitally speed sensorless control system for induction motor with direct torque control (DTC). Some drawbacks of the classical DTC are the relatively large torque ripple in a low speed range and notable current pulsation during steady state. They are reflected speed response and increased acoustical noise. In this paper, the DTC quick response are preserved at transient state, while better qualify steady state performance is produced by space vector modulation (SVM). The system are closed loop stator flux and torque observer for wide speed range that inputs are currents and voltages sensing of motor terminal, model reference adaptive control (MRAC) with rotor flux linkages for the speed fuming signal at low speed range, two hysteresis controllers and optimal switching look-up table. Simulation results of the suggest system for the 2.2 [kW] general purposed induction motor are presented and discussed.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1996년도 추계학술대회 논문
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• pp.6-10
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• 1996

This paper presents an overview of research results obtained by the authors in a series of publications. Methods are developed both for time-varying and time-invariant for linear and nonlinear. for time domain and frequency domain . and for discrete-time and continuous-time systems. Among the topics presented are: 1. Learning control based on integral control concepts applied in the repetition domain. 2. New algorithms that give improved transient response of the indirect adaptive control ideas. 4. Direct model reference learning control. 5 . Learning control based frequency domain. 6. Use of neural networks in learning control. 7. Decentralized learning controllers. These learning algorithms apply to robot control. The decentralized learning control laws are important in such applications becaused of the usual robot decentralized controller structured.

• 조명전기설비학회논문지
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• 제25권5호
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• pp.22-33
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• 2011

An induction motor operated with a conventional direct self controller(DSC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic controller(FLC) is used in conjection with DSC to minimize these problems. A FLC chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determinated by observing the vector diagram of flux and currents. This paper proposes hybrid fuzzy controller for direct torque control(DTC) of induction motor drives. The speed controller is based on adaptive fuzzy learning controller(AFLC), which provide high dynamics performances both in transient and steady state response. Flux position, error in flux magnitude and error in torque are used as FLC state variables. The speed is estimated with model reference adaptive system(MRAS) based on artificial neural network(ANN) trained on-line by a back-propagation algorithm. This paper is controlled speed using hybrid fuzzy controller(HFC) and estimation of speed using ANN. The performance of the proposed induction motor drive with HFC controller and ANN is verified by analysis results at various operation conditions.