• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.1150-1155
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• 2006

In a heating control system, the indoor temperature controller transfers temperature signals inputed from the temperature sensor and the user to the valve controller. The valve controller recieves these signals then the valve controller controls the valve driving motor on two position control and controls the indoor temperature. When setting up a new valve driving motor from a long distance it is necessary to set up a new valve controller. But occasionary, due to construction, it is impossible to wire between the existing valve controller and the new valve controller. In this situation, the new and existing valve controllers can communicate via power line communication. In this paper it is proposed heating control system controls on two position control via power line communication.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.102-108
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• 2001

In this paper, an active noise controller for a communication headset was designed. In a communication headset, there exist information signals such as voices from the end for the communication line as well as also, undesirable noises with are induced by external noise sources such as engine noises. Therefore, it is necessary to reduce the external noises for clear hearing of the communication signals. This problem was solved by robust H(sub)$\infty$ controller to reduce noise and a compensator for information signals The designed controller was implemented using TMS320C31 DSP Op-amp, and several experiments were performed to verify its performance. The results showed that the controller reduces the undesirable noises sufficiently, while communication signals are not reduced.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.91-93
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• 2007

This paper presents multi-PI controller of IPMSM drive using fuzzy and neural-network. In general, PI controller in computer numerically controlled machine process fixed gain. To increase the robustness, fred gain PI controller, Multi-PI controller proposes a new method based fuzzy and neural-network. Multi-PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.43-59
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• 2019

The Traffic controller currently used in Korea is a switch control system that directly transfers 220V of high voltage to traffic lights one to one. This method requires a lot of cables, and there are concerns about electric shock. Accordingly, Korea Road Traffic Authority added the digital communication signal controller standard using digital communication method to the standard specification of the communication signal controller of the National Police Agency. Based on these specifications, this paper intended to develop digital communication call controllers. In addition, it was verified that even if the digital communication signal controller and analogue communication call controller were mixed, they could operate in the signal control system currently in operation.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.53-55
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• 2006

This paper presents self tuning PI controller of IPMSM drive using neural network. NNPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.88-90
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• 2007

This paper is proposed high performance speed control using AFNN controller. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. The control performance of the AFNN controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.582-588
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• 2001

The Multiple Model/Controller IMC(MMC-IMC) is a model-based control method which uses a set of model/controller pairs rather than a single model/controller to handle all possible operating conditions in the IMC control structure. During operation, one model/controller pair that best fit, for current plant situation is chosen by the switching algorithm. The major drawback of the switching controller is the bad transient performance due to the model error and the use fo linear controller for nonlinear plants. In this paper, we propose a method that transient response of the MMC-IMC using two recurrent neural networks. Simulation result shows that the proposed method represents better performance than the usual MMC-IMC`s.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1459-1461
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• 2005

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 fuzzy-neural networks(FNN) controller that is implemented using fuzzy control and neural networks. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. Simulation results are presented to show the validity of the proposed algorithm

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1453-1455
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• 2005

This paper presents self tuning PI controller of IPMSM drive using neural network. Self tuning PI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.583-585
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• 1999

This paper presents the controller of multiple DC motors using the network. This controller has been built with 16-bits one chip microprocessor (87C196CA) which includes the integrated CAN serial communication and position control for two motors. Since only one microprocessor is needed, the proposed controller is not only cost effective but also powerful. The system is composed of one main controller, trajectory planner, and the other sub controller, position controller. The main controller which has been built using Visual Basic programming on the Pentium PC, generates the trajectory and then transmits it to the sub controller. The trajectory transmitted from the PC will be processed by the sub controller. Two motors are controlled using the conventional position control, PID, to reach them the same target position but with different velocities at the same time. The communications between the main controller and sub controller is performed through the RS-232 or the CAN communication The CAN would be safer and faster than serial communication network since it has non-destructive bitwise arbitration specification. In this paper, we consider the CAN communications generally and then show the usefulness of the proposed controller by demonstrating position control of two DC motors.