• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.65.2-65
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• 2002

This paper is concerned with the accurate position control of a rodless pneumatic cylinder using On/Off solenoid valve. A novel Intelligent Modified Pulse Width Modulation(MPWM) is newly proposed. The control performance of this pneumatic cylinder depends on the external loads. To overcome this problem , switching of control parameter using artificial neural network is newly proposed, which estimates external loads on rodless pneumatic cylinder using this training neural network. As an underlying controller, a state feedback controller using position, velocity and acceleration is applied in the switching control the system. The effectiveness of the proposed control algorithms are demonstrated...on/off solenoid valve, load estimation, MPWM, Artificial neural network.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.543-548
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• 2000

In this study, an interactive programming method for robot in electronic part assembly task is proposed. Many of industrial robots are still taught and programmed by a teach pendant. The robot is guided by a human operator to the desired application locations. These motions are recorded and are later edited, within the robotic language using in the robot controller, and play back repetitively to perform robot task. This conventional teaching method is time-consuming and somewhat dangerous. In the proposed method, the operator teaches the desired locations on the image acquired through CCD camera mounted on the robot hand. The robotic language program is automatically generated and downloaded to the robot controller. This teaching process is implemented through an off-line programming software. The OLP is developed for an robotic assembly system used in this study. In order to transform the location on image coordinates into robot coordinates, a calibration process is established. The proposed teaching method is implemented and evaluated on an assembly system for soldering electronic parts on a circuit board. A six-axis articulated robot executes assembly task according to the off-line teaching in the system.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.3
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• pp.397-403
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• 2012

This paper describes a control method of turn-on/off angles to improve the efficiency of the switched reluctance generator(SRG) with a power closed-loop control system, and the inner-loop of the system is current hysteresis control. The SRG control system is constituted by the PI power controller and the two-level current hysteresis controller. By measuring and analyzing the system losses of different reference powers, speeds and turn-on/off angles, selection strategy of optimal turn-on/off angles is discussed. The proposed method is simple, reliable, and easy to achieve.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.4
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• pp.77-83
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• 1994

In this paper, an optimal control of first order systems is discussed. The control system comprises a main controller and an auxiliary controller. The main controller is designed based on the LQ control scheme including an integrator to remove the off-set. The non-linear auxiliary controller is added parallely to the main controller to obtain a finite time settling control. The control parameters under variation of the system and various coefficients of the performance indices are computed numerically, and the control responses for the system with the proposed controllers demonstrated the usefulness of the control method.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.986-988
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• 2022

본 연구는 전기전자기기를 비접촉 ON/OFF제어와 기기의 수명연장을 개선 시키기위해 전기전자기기에 다용도로 활용되는 제어컨트롤러 모듈인 PLC(Programmable Logic Controller)의 입력측에 마이크로컨트롤러와 AI 비젼카메라를 설치하여, 비접촉 ON/OFF 제어에 관한 아이디어 제시하고, 이를 기반으로 구현하였다. 구현 결과 단순 I,O 신호에 의한 제어와는 다르게 이미지 인식을 구체적으로 구분하여 센싱하고, 다양한 인식 구분을 위해 머신러닝 기반으로 AI 비젼카메라를 학습시킨 결과 물체 및 색깔 구분에 따라서 전기전자기기를 제어 할 수 있었으며, 접촉이 아닌 비접촉 ON/OFF 제어가 간단하게 구현되어, 전기전자기기 수명연장도 기대 할 수 있게 되었다..

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.279-281
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• 2006

In this paper, we study an approach to design a self-tuning Fuzzy-PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of conversional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. The above problems are solved by adapting Fuzzy-PI controller for the fire angle control of rectifier.[7] The performance of the Fuzzy-PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain the optimal scaling factors of the Fuzzy-PI controller by Genetic Algorithms. In order to improve Fuzzy-PI controller, we adopt FIS to tune the scaling factors of the Fuzzy-PI controller on line. A comparative study has been performed between Fuzzy-PI and self-tuning Fuzzy-PI controller, to prove the superiority of the proposed scheme.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.677-680
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• 2003

The control of the SRM(Switched Reluctance Motor) is usually based on the non-linear inductance profiles with positions. So determination of optimal switching angle is very different. we present self-tuning control of SRM for maximum torque and efficiency with phase current and shaft position sensor During the sample time, micro-controller checks the number of pre-checked pulse. After micro-controller calculates between two data, it move forward or backward turn-off angle. When the turn-off angle is fixed optimal turn-off angle, turn-on angle moves forward or backward by a step using self-tuning control method. And then, optimal turn-off angle is searched once again. As such a repeating process, turn-on/off angle is moves automatically to obtain the maximum torque and efficiency. The experimental results are presented to validate the self-tuning algorithm.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.3
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• pp.48-54
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• 2016

This paper proposes a prediction model of air traffic controller's take-off clearance under mixed mode runway operations. The proposed model has its purpose on the better prediction of the air traffic controller's clearance on take-offs of departure aircraft by considering various factors. For this purpose, support vector machine classification algorithm is used for the proposed model. The proposed model is applied to real air traffic operations to demonstrate its performances.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.3
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• pp.107-113
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• 2001

This paper deals with speed control of DC servo motor using a PID controller with a gain tuning based on a Back-Propagation(BP) Learning Algorithm. Conventionally a PID controller has been used in the industrial control. But a PID controller should produce suitable parameters for each system. Also, variables of the PID controller should be changed according to environments, disturbances and loads. In this paper described by a experiment that contained a method using a PID controller with a gain tuning based on a Back-Propagation(BP) Learning Algorithm, we developed speed characteristics of a DC servo motor on variable loads. The parameters of the controller are determined by neural network performed on on-line system after training the neural network on off-line system.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.4
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• pp.15-26
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• 1998

Full car model is needed for investigating as a entire dynamics of vehicle. In this study, 7DOF of full car model's dynamics is selected. This paper proposes the output feedback controller based on optimal control theory. Input data and output data from the optimal controller are used for neural network system identification of the suspension system. To do system identification, neural network which has robustness against nonlinearities and disturbances is adapted. This study uses back-propagation algorithm to train a multil-layer neural network. After obtaining a neural network model of a suspension system, a neuro-controller is designed. Neuro-controller controls suspension system with off-line learning method and multistep ahead prediction model based on the neural network model and a neuro-controller. The optimal controller and the neuro-controller are designed and then, both performances are compared through. For simulation, sinusoidal and rectangular virtual bumps are selected.