• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.572-580
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• 2013

IEEE 802.15.4e is a prospective standard for low latency control application in industries. This paper proposes a framework to evaluate the closed loop IEEE 802.15.4e based WNCS performance. The framework consists of two models: closed loop control system model and network model. The network model focuses on the PHY parameters of wireless link and takes the channel parameters into consideration. The PHY model combining with MAC model gives the control system model the probability of packet loss in a super-frame. In addition, redundancy mechanism is considered in IEEE 802.15.4e to reduce to data frame loss probability. The simulation is implemented in Matlab, PHY model takes the channel parameters from empirical results. Hence our evaluation gives insight into behavior of WNCS in different environments and it provides us a tool to design wireless network to achieve a good performance for control system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.7
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• pp.15-25
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• 2011

This proposes an online loss minimization algorithm for series PI(SPI) based interior permanent magnet synchronous motor(IPMSM) drive to yield high efficiency and high dynamic performance over wide speed range. The loss minimization algorithm is developed based on the motor model. In order to minimize the controllable electrical losses of the motor and thereby maximize the operating efficiency, the d-axis armature current is controlled optimally according to the operating speed and load conditions. For vector control purpose, a SPI is used as a speed controller which enables the utilization of the reluctance torque to achieve high dynamic performance as well as to operate the motor over a wide speed range. Also, this paper proposes current control of model reference adaptive fuzzy controller(MFC), and estimation of speed using artificial neural network(ANN) controller. The proposed efficiency optimization control, SPI, MFC, ANN in this paper is applied to IPMSM drive system, the validity of this paper is proved by analyzing response characteristics in variety operating conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.385-391
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• 2005

As the Internet real-time multimedia applications increases, the bandwidth available to TCP connections is oppressed by the UDP traffic, result in the performance of overall system is extremely deteriorated. Therefore, developing a new transmission protocol is necessary. The TCP-friendly algorithm is an example satisfying this necessity. The TCP-Friendly Rate Control (TFRC) is an UDP-based protocol that controls the transmission rate that is based on the available round trip time (RTT) and the packet loss rate (PLR). In the data transmission processing, transmission rate is determined based on the conditions of the previous transmission period. If the one-step ahead predicted values of the control factors are available, the performance will be improved significantly. This paper proposes a prediction model of transmission rate control factors that will be used in the transmission rate control, which improves the performance of the networks. The model developed through this research is predicting one-step ahead variables of RTT and PLR. A multiplayer perceptron neural network is used as the prediction model and Levenberg-Marquardt algorithm is used for the training. The values of RTT and PLR were collected using TFRC protocol in the real system. The obtained prediction model is validated using new data set and the results show that the obtained model predicts the factors accurately.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.69-74
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• 1999

Adaptive algorithms based on gradient adaptation have been extensively investigated and successfully joined with active noise/vibration control applications. The Filtered-X LMS algorithm became one of the basic feedforward algorithms in such applications, but is not fully understood yet. Effects of cancellation path model on the Filtered-X LMS algorithm have investigated and some useful properties related to stability were discovered. Most of the results stated that the error in the cancellation path model is undesirable to the Filtered X LMS. However, we started convergence analysis of Filtered-X LMS based on the assumption that erroneous model does not always degrade its performance. In this paper, we present a way of optimizing the cancellation path modern in order to enhance the convergence speed by introducing intentional phase error. Carefully designed intentional phase error enhances the convergence speed of the Filtered X LMS algorithm for pure tone noise suppression application without any performance loss at steady state.

• Journal of Navigation and Port Research
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• v.44 no.5
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• pp.423-429
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• 2020

A ship's automatic steering system is the basis for addressing control difficulties related to course-changing and course-keeping during navigation through heading angle control, and is a link in realizing unmanned and autonomous ships. This study proposes a robust RCGA-based linear active disturbance rejection controller (LADRC) design method considering environmental disturbances, measurement noise, and model uncertainties in designing a ship heading controller for use when the ship is sailing. The LADRC consisted of a transient profile, a linear extended state observer, and a PD controller. The control gains in the LADRC with the linear extended state observer were adjusted by RCGAs to minimize the integral of the time-weighted absolute error (ITAE), which is an evaluation function of the control system. The proposed method was applied to ship heading control, and its effectiveness was validated by comparing the propulsive energy loss between the proposed method and a conventional linear PD controller. The simulation results showed that the proposed method had the advantages of lower propulsive energy loss, more robustness, and higher tracking precision than the conventional linear PD controller.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.51-54
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• 2005

Generator efficiency optimization is important for economic saving and environmental pollution reduction. In general, the machine loss can be reduced by the decreasing the flux level, resulting in the significant reduction of the core loss. This paper proposesan model-based controller is used to decrement the excitation current component on the basis of measured stator current and machine parameters and the q-axis current component controls the generator torque, by which the speed of the induction generator iscontrolled according to the variation of the wind speed in order to produce the maximum output power. The generator reference speed is adjusted according to the optimum tip-speed ratio. The generated power flows into the utility grid through the back-to-back PWM converter. The grid-side converter controls the dc link voltage and the line-side power factor by the q-axis and the d-axis current control, respectively. Experimental results are shown to verify the validity of the proposed scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.6
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• pp.1047-1054
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• 2007

This paper presents a high efficiency direct instantaneous torque control (DITC) of Switched Reluctance Motor(SRM) based on the nonlinear model. The DITC method can reduce the high inherent torque ripple of SRM drive system, but drive efficiency is somewhat low due to the high current and switching loss during commutations. In order to reduce a torque ripple, a fast torque reference trajectory is selected at every instantaneous rotor position. Based on the nonlinear model of SRM, the developing torque by one phase is fixed and the other phase is regulated for minimum switchings of phase switch and variation of torque. The switching during commutation can be reduced and fast commutation can be obtained in the proposed method. As a result, drive efficiency could be improved as well as torque ripple reduction. The validity of proposed method is verified by computer simulations and comparative experiments.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.123-130
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• 2024

This paper proposes an EMPC (Explicit Model Predictive Controller) for temperature tracking control based on heat load prediction by an ESO (Extended State Observer) for a variable cooling circulation system with multiple indoor units connected to one outdoor unit. In this system, heat transfer and heat loss relative to the input temperature are modeled using system dynamics. Using this model, we design an EMPC based on an ESO that is robust to temperature changes and depends on airflow. To determine the stability of both the controller and the observer, asymptotic stability is verified through Lyapunov stability analysis. Finally, to validate the performance of the proposed controller, simulations are conducted under three scenarios with varying airflow, set temperature, and heat load.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.241-248
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• 2007

The accuracy of all the schemes that belong to vector controlled induction machine drives is strongly affected by parameter variations. The aim of this paper is to examine iron losses and magnetic saturation effect in sensorless vector control of induction machines. At first, an approach to induction machine modelling and vector control scheme, which account for both iron loss and saturation, is presented. Then, a model reference adaptive system (MRAS) based speed estimator is developed. The speed estimation is modified in such a way that iron losses and the variation in the saturation level are compensated. Thus by substituting an artificial neural network flux estimator into the MRAS speed estimator. Experimental results are presented to verify the effectiveness of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.967-982
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• 2011

This paper presents a FTNCS (Fault-Tolerant Networked Control System) that can tolerate control surface failure and packet delay/loss in an UAV (Unmanned Aerial Vehicle). The proposed method utilizes the benefits of self-diagnosis by smart actuators along with the control allocation technique. A smart actuator is an intelligent actuation system combined with microprocessors to perform self-diagnosis and bi-directional communications. In the event of failure, the smart actuator provides the system supervisor with a set of actuator condition data. The system supervisor then compensate for the effect of faulty actuators by re-allocating redundant control surfaces based on the provided actuator condition data. In addition to the compensation of faulty actuators, the proposed FTNCS also includes an efficient algorithm to deal with network induced delay/packet loss. The proposed algorithm is based on a Lagrange polynomial interpolation method without any mathematical model of the system. Computer simulations with an UAV show that the proposed FTNCS can achieve a fast and accurate tracking performance even in the presence of actuator faults and network induced delays.