• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.441-442
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• 2015

This paper proposes a new single-phase seven-level grid-connected inverter. Operational principle with switching function are analyzed. A digital proportional-integral current-control algorithm was implemented in a TMS320F28335 DSP to keep the current injected into the grid sinusoidal. To verify the performance of the proposed inverter, PSIM simulation and experimental results are also shown in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.5-49
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• 2001

The Proportional-Integral-Derivative control scheme is widely used in industries. This paper investigates an alternative control paradigm for controlling lightweight Cartesian robot arms. Fuzzy PI control is used and validated experimentally by comparing performance with a conventional PID control algorithm. The results show the effectiveness of the fuzzy PI control. The fuzzy control shows superior performance in transient response over the conventional one.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.13-23
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• 2016

Many traffic centers are highly hesitant in employing existing Automatic Incident Detection Algorithms due to high false alarm rate, low detection rate, and enormous effort taken in maintaining algorithm parameters, together with complex algorithm structure and filtering/smoothing process. Concerns grow over the situation particularly in Freeway Incident Management Area This study proposes a new algorithm and introduces a novel concept, the Displaced Flow Index (DiFI) which is similar to a product of relative speed and relative occupancy for every execution period. The algorithm structure is very simple, also easy to understand with minimum parameters, and could use raw data without any additional pre-processing. To evaluate the performance of the DiFI algorithm, validation test on the algorithm has been conducted using detector data taken from Naebu Expressway in Seoul and following transferability tests with Gyeongbu Expressway detector data. Performance test has utilized many indices such as DR, FAR, MTTD (Mean Time To Detect), CR (Classification Rate), CI (Composite Index) and PI (Performance Index). It was found that the DR is up to 100%, the MTTD is a little over 1.0 minutes, and the FAR is as low as 2.99%. This newly designed algorithm seems promising and outperformed SAO and most popular AIDAs such as APID and DELOS, and showed the best performance in every category.

• Journal of Power Electronics
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• v.6 no.4
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• pp.322-329
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• 2006

In the last decade, the increasing restrictions imposed on the exhaust emissions from internal combustion engines and traffic limitations have increased the development of electrical propulsion systems for automotive applications. The goal of electrical and hybrid vehicles is the reduction of global emissions, which in turn leads to a decrease in fuel resource exploitation. This paper presents a novel approach for control of Induction Motors (IM) using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the Proportional Integral Controller (PI-Controller). The overall system is simulated under various operating conditions. The use of PSO as an optimization algorithm makes the drive robust and insensitive to load variation with faster dynamic response and higher accuracy. The system is tested under variable operating conditions. The simulation results show a positive dynamic response with fast recovery time.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1191-1194
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• 1987

This paper presents a method for computing the powers and inverse of an element in GF($2^m$). This method is based on the squaring algorithm $A^2=\sum\limits_{i=0}^{2m-2}P_i$, where $Pi={\alpha}_{i/2}$ if i is even, Pi=0 otherwise, derived from the multiplication algorithm for two elements in GF($2^m$). The powers and inverses in GF($2^m$) for m=2, 3, 4,5 were obtained using computer program, and used in circuit realization of Galois switching function. The squaring and inverse generating circuits are also shown.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.96-102
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• 1999

Sensorless speed estimation in induction motor systems is one of the most control engineers. Based on the estimated speed the vector control has been applied to the high precision torque control however most speed estimation methods use adaptive scheme so that it takes long time to estimate the speed. Thus the adaptive estimation scheme is not effective to the induction motor which requires short sampling time. In this paper a new linearized equation of induction motor system is proposed and a sensorless speed estimation algorithm based on observation techniques is developed. First the nonlinear induction motor equation is linearized at an equilibrium point. Second a proportional integral(PI) observer is applied to estimate the speed state in the induction motor system. Finally simulation results will assure the effectiveness of the new linearized equation and the sensorless estimation algorithm by using PI observer in the nonlinear induction motor system.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.403-405
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• 1999

The model reference adaptive control(MRAC) algorithm is applied to the speed control of an inverter driven permanent magnet brushless do motor MRAC is compared to a standard PI controller. Applying this algorithm has also been proved by simulations that quick speed response without over-shoot could be obtained for the motor system with variable parameters. Simulation results show that the adaptive controller is superior to the PI controller.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.838-840
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• 1997

This presents a design method for fuzzy logic controllers of TCSC using genetic algorithm. Fuzzy logic controllers are applied to damp the dynamic disturbances sum as sudden changes of AC system loads. The dynamic performances of fuzzy logic controllers are compared with those of PI controllers. The simulation results show that dynamic performances of fuzzy controllers have better response than those of PI controllers when the AC system load changes.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.8 no.1
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• pp.65-75
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• 1996

A pilot plant, which is simplified the hot water heating control system of a large scale residential building, is used to investigate the effects of control methods and operating conditions on the system performance and to compare control characteristics. Digital variable structure controller(DVSC) and digital PI controller are implemented to control the speed of the circulating pump for the pilot plant using PC. For the DVSC, a control algorithm is suggested, which using a nonlinear sliding surface and a PID sliding surface outside and inside of output error boundary layer, respectively. Smith predictor algorithm is used for the compensation of long dead time. The suggested DVSC yields improved control performance compared with existing DVSC using linear sliding surface only. the system responses with the suggested DVSC shows good responses without overshoot for various operating conditions and robust under external disturbances compared with digital PI controller.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.192-194
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• 1996

This paper propose an optimal scaling gain tuning method of the fuzzy PI controller using Genetic Algorithm(GA). Scaling gains can reflect the control resolution and fuzziness of input/output variables. By the scaling gain method, the design of a fuzzy logic controller(FLC) can be simplified without affecting the system performance in comparison with multi-decision table method. In designing a fuzzy logic controller, the analytic approach method for the optimization is unavailable. Therefore GA is excellent optimization algorithms for scaling gain tuning. Using this optimal scaling gain tuning method, a good performance can be achieved both in transient and steady state.