• The Transactions of the Korean Institute of Electrical Engineers B
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• v.50 no.12
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• pp.609-614
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• 2001

This paper presents a multi output converter system that controls, simultaneously and independently, the separate Buck converter and Boost converter with the different specification by one DSP digital controller. As two separate converters are regulated by only one DSP, it is possible to achieve the simple digital control circuit for regulating multi output DC-DC converter. By setting the software switch state, PI and Fuzzy controller can be applied as a controller for each converter without any change of hardware. Also, it is included the control characteristics comparison between PI and Fuzzy controller. The control characteristics of each PWM DC-DC converter is validated by experimental results.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1923-1924
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• 2006

본 논문은 HVAC(heating, ventilating, and air conditioning) 시스템에 대하여 Multi Fuzzy 제어기 설계를 제안한다. HVAC 시스템은 Compressor(압축기), Condenser(응축기), Evaporator(증발기), Expansion Valve 로 구성되며, 각각의 기기에 대한 제어가 독립적으로 이루여져 있다. 기존의 제어가 한 제어기를 사용한 단일방식으로 이루어지다보니 HVAC 시스템의 특성인 냉매의 상태가 달라지면 시스템 전반적으로 그 영향이 파급되는 부분까지 고려를 해 주지 못하고, 제어기의 성능이 효율적이지 못했다. 본 논문에서는 비선형성이 강하고 불확실하며 복잡한 시스템을 쉽게 제어할 수 있는 Fuzzy 제어기를 구성하여 Expansion Valve 와 Compressor 에서 동시에 제어하는 Multi 제어기를 설계한다. 제안된 Multi Fuzzy 제어기는 HVAC 시스템의 효율성과 안정성에 기초하여, 과열도와 저압을 제어한다.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.277-278
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• 2007

본 논문은 HVAC(heating, ventilating, and air conditioning) 시스템에 대해 Particle Swarm Optimization(PSO) 알고리즘을 이용하여 최적화된 Multi-Fuzzy 제어기 설계를 제안한다. HVAC 시스템의 효율과 안정도에 결정적인 영향을 미치는 과열도와 저압(증발기의 압력)을 제어하기 위해, 3대의 Expansion Valve 와 1대의 Compressor 에서 동시에 제어하는 Multi-Fuzzy 제어기를 설계한다. 그리고 최적화 알고리즘 중 하나인 사회적인 행동양식을 기반한 PSO 알고리즘을 이용하여 설계된 Multi-Fuzzy 제어기를 최적화한다. 시뮬레이션의 결과 비교를 통해, 대표적인 최적화 알고리즘인 유전자 알고리즘을 사용한 최적화된 제어기와 제안한 PSO 알고리즘을 이용한 최적화된 제어기의 성능을 평가한다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2451-2460
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• 2000

In order to minimize straightness error of deflected shaft, a geometric adaptive straightness controller system is studied. A multi-step straightening and a three-point bending process have been developed for the geometric adaptive straightness controller. Load-deflection relationship, on-line identification of variations of material properties, on-line springback prediction, and real-time hydraulic control methodology are studied for the three-point bending process. By deflection pattern analysis and fuzzy self-learning method in the multi-step straightening process, a straightening point and direction, desired permanent deflection and supporting condition are determined. An automatic straightening machine has been fabricated for rack bars by using the developed ideas. Validity of the proposed system is verified through experiments.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.203-207
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• 2001

This paper presents a multi output converter system that controls, simultaneously and independently, the separate Buck converter and Boost converter with the different specification by one DSP digital controller. As two separate converters are regulated by only one DSP, it is possible to achieve the simple digital control circuit for regulating the multi output DC-DC converter. By setting the software switch state, PI or Fuzzy controller can be applied as a controller for each converter without any change of hardware. Also, PI and Fuzzy control characteristics of each DC-DC converter is validated by experimental results.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.42-49
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• 2001

In This paper, we present a collaborative method for material delivery using a distributed vehicle agents system. Generally used AGV(Autonomous Guided Vehicle) systems in FA(Factory Automation) require extraordinary facilities like guidepaths and landmarks and have numerous limitations for application in different environments. Moreover in the case of controlling multi vehicles, the necessity for developing corporation abilities like loading and unloading materials between vehicles including different types is increasing nowadays for automation of material flow. Thus to compensate and improve the functions of AGV, it is important to endow vehicles with the intelligence to recognize environments and goods and to determine the goal point to approach. In this study we propose an interaction method between hetero-type vehicles and adaptive fuzzy logic controllers for sensor-based path planning methods and material identifying methods which recognizes color. For the purpose of carrying materials to the goal, simple color sensor is used instead of intricate vision system to search for material and recognize its color in order to determine the goal point to transfer it to. The technique for the proposed method will be demonstrated by experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1447-1456
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• 2011

In this paper, we propose a T-S fuzzy feedback linearization method for controlling a non-linear system with multi-input, and the method is applied for trajectory tracking control of wheeled mobile robot. First, an error dynamic equation of wheeled mobile robot is represented by a T-S fuzzy model, and then the T-S fuzzy model is transformed to a linear control system through the nonlinear fuzzy coordinate change and the nonlinear state feedback input. Simulation results showed that the trajectory tracking controller by using the proposed multi-input feedback linearization method gives better performance than the trajectory tracking controller by using the PDC(Parallel Distributed Compensation) method for controlling the T-S Fuzzy system.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.4
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• pp.349-358
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• 2013

In this paper, the sensorless MPPT algorithm is proposed where the performance of varied duty ratio change has been improved using multi-layer neuro-fuzzy that aligns with neuro-fuzzy based optimized membership function. Since the change of duty ratio of sensorless MPPT is varied by using the neuro-fuzzy, the MPPT response speed is faster than the convectional method and is able to reduce the steady-state ripple. The neuro fuzzy controller has the response characteristics which is superior to the existing fuzzy controller, because of the usage of the optimal width of the fuzzy membership function. The effectiveness of the proposed method has been verified by simulations and experimental results.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.7 s.94
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• pp.1813-1822
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• 1993

An algorithm of fuzzy variable structrue control is proposed to design a closed loop fuel-injection system for the emission control of automotive gasoline engines. Fuzzy control is combined with sliding control at the switching boundary layer to improve the chattering of the stoichiometric air to fuel ratio. Multi-staged fuzzy rules are introduced to improve the adaptiveness of control system for the various operating conditions of engines, and a simplified technique of fuzzy inference is also adopted to improve the computational efficiency based on nonfuzzy micro-processors. The proposed method provides an effective way of engine controller design due to its hybrid structure satisfying the requirements of robustness and stability. The great potential of the fuzzy variable structure control is shown through a hardware-testing with an Intel 80C186 processor for controller and a typical engine-only model on an AD-100 computer.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.34-39
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• 2013

This paper proposes the implementation of robust fuzzy controller for designing intelligent wind farm and mitiagating the fluctuation of wind power generator. The existing researches are limited to individual wind turbine with variable speed so that it is necessary to study the multi-agent wind turbine power system. The scopes of these studies include from the arrangements of each power turbine to the control algorithms for the wind farm. For solving these problems, we introduce the composition of intelligent wind farm and use the T-S (Takagi-Sugeno) fuzzy model which is suitable for designing fuzzy controller. The control object in wind farm enables the minimizing the fluctuation of wind power generator. Simulation results for wind fram which is modelled as mathematically are demonstrated to visualize the feasibility of the proposed method.