• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.318-325
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• 2008

HomePlug AV(HPAV) is the standard for distribution of Audio/video content as well as data within the home by using the power line. It uses a hybrid access mechanism that combines TDMA with CSMA/CA for MAC technology. The CSMA/CA protocol in HPAV has two main control blobs that can be used for access control: contention window(CW) size and deferral counter(DC). In this paper, we extensively investigate the impacts of CW and DC on performance through simulations, and propose an adaptive mechanism that adjusts the CW size to enhance the throughput in HPAV MAC. We find that the CW size is more influential on performance than the DC. Therefore, to make controlling the network easier, our proposal uses a default value of DC and adjusts the CW size. Our scheme simply increases or decreases the CW size if the network is too busy or too idle, respectively, We compare the performance of our proposal with those of the standard and other competitive schemes in terms of throughput and fairness. Our simulation and analysis results show that our adaptive CW mechanism performs very well under various scenarios.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.191-200
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• 2022

Constrained Application Protocol (CoAP) is a standardized protocol by the Internet Engineering Task Force (IETF) for the Internet of things (IoT). IoT devices have limited computation power, memory, and connectivity capabilities. One of the significant problems in IoT networks is congestion control. The CoAP standard has an exponential backoff congestion control mechanism, which may not be adequate for all IoT applications. Each IoT application would have different characteristics, requiring a novel algorithm to handle congestion in the IoT network. Unnecessary retransmissions, and packet collisions, caused due to lossy links and higher packet error rates, lead to congestion in the IoT network. This paper presents an adaptive congestion control protocol for CoAP, Adaptive Congestion Control with a Backoff algorithm (ACCB). AACB is an extension to our earlier protocol AdCoCoA. The proposed algorithm estimates RTT, RTTVAR, and RTO using dynamic factors instead of fixed values. Also, the backoff mechanism has dynamic factors to estimate the RTO value on retransmissions. This dynamic adaptation helps to improve CoAP performance and reduce retransmissions. The results show ACCB has significantly higher goodput (49.5%, 436.5%, 312.7%), packet delivery ratio (10.1%, 56%, 23.3%), and transmission rate (37.7%, 265%, 175.3%); compare to CoAP, CoCoA+ and AdCoCoA respectively in linear scenario. The results show ACCB has significantly higher goodput (60.5%, 482%,202.1%), packet delivery ratio (7.6%, 60.6%, 26%), and transmission rate (40.9%, 284%, 146.45%); compare to CoAP, CoCoA+ and AdCoCoA respectively in random walk scenario. ACCB has similar retransmission index compare to CoAp, CoCoA+ and AdCoCoA respectively in both the scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1681-1684
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• 2014

In this paper, in the ventilation system of coal-fired power boilers can measure in real time the fan stall mechanism is all about. The fan stall guard system of boiler airing system of the class of 500MW capacity to protect fan. But because confidence is loosed and operation is influenced by frequent fault of fan stall guard system, confidence is improved by substituting DCS Logic for it.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.593-603
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• 2019

In wearable healthcare systems, sensor devices can be deployed in places around the human body such as the stomach, back, arms, and legs. The sensors use tiny batteries, which have limited resources, and old sensor batteries must be replaced with new batteries. It is difficult to deploy sensor devices directly into the human body. Therefore, instead of replacing sensor batteries, increasing the lifetime of sensor devices is more efficient. A transmission power control (TPC) algorithm is a representative technique to increase the lifetime of sensor devices. Sensor devices using a TPC algorithm control their transmission power level (TPL) to reduce battery energy consumption. The TPC algorithm operates on a closed-loop mechanism that consists of two parts, such as sensor and sink devices. Most previous research considered only the sink part of devices in the closed-loop. If we consider both the sensor and sink parts of a closed-loop mechanism, sensor devices reduce energy consumption more than previous systems that only consider the sensor part. In this paper, we propose a new approach to consider both the sensor and sink as part of a closed-loop mechanism for efficient energy management of sensor devices. Our proposed approach judges the current channel condition based on the values of various body sensors. If the current channel is not optimal, sensor devices maintain their current TPL without communication to save the sensor's batteries. Otherwise, they find an optimal TPL. To compare performance with other TPC algorithms, we implemented a TPC algorithm and embedded it into sensor devices. Our experimental results show that our new algorithm is better than other TPC algorithms, such as linear, binary, hybrid, and ATPC.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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• pp.110-114
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. In this paper maximum torque control of IPMSM drive using artificial intelligent(AI) controller is proposed. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using adaptive learning mechanism fuzzy neural network(ALM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the experimental results to verify the effectiveness of AI controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.1
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• pp.29-37
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• 2006

Precise control of interior permanent magnet synchronous motor(IPMSM) over wide speed range is an engineering challenge. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using learning mechanism-fuzzy neural network(LM-FNN) and ANN(artificial neural network) control. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility md numerical processing capability. Also, this paper proposes speed control of IPMSM using LM-FNN and estimation of speed using artificial neural network controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. 'The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. Analysis results to verify the effectiveness of the new hybrid intelligent control proposed in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4819-4834
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• 2015

The spectral efficiency of cellular networks can be improved when proximate users engage in device-to-device (D2D) communications to communicate directly without going through a base station. However, D2D communications that are not properly designed may generate interference with existing cellular networks. In this paper, we study resource allocation and power control to minimize the probability of an outage and maximize the overall network throughput. We investigate three power control-based schemes: the Partial Co-channel based Overlap Resource Power Control (PC.OVER), Fractional Frequency Reuse based Overlap Resource Power Control (FFR.OVER) and Fractional Frequency Reuse based Adaptive Power Control (FFR.APC) and also compare their performance. In PC.OVER, a certain portion of the total bandwidth is dedicated to the D2D. The FFR.OVER and FFR.APC schemes combine the FFR techniques and the power control mechanism. In FFR, the entire frequency band is partitioned into two parts, including a central and edge sub-bands. Macrocell users (mUEs) transmit using uniform power in the inner and outer regions of the cell, and in all three schemes, the D2D receivers (D2DRs) transmit with low power when more than one D2DRs share a resource block (RB) with the macrocells. For PC.OVER and FFR.OVER, the power of the D2DRs is reduced to its minimum, and for the FFR.APC scheme, the transmission power of the D2DRs is iteratively adjusted to satisfy the signal to interference ratio (SIR) threshold. The three schemes exhibit a significant improvement in the overall system capacity as well as in the probability of a user outage when compared to a conventional scheme.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10d
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• pp.236-239
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• 2006

무선 센서 네트워크에서는 에너지 제약이라는 특징 때문에 에너지 효율과 관련된 많은 연구가 진행되고 있지만 대부분의 연구는 에너지를 보존하기 위해 센서노드의 작업을 줄이는 소극적인 방식을 취한다. 이에 반해 파워 컨트롤 기법은 전송 파워를 조절하여 불필요한 에너지 소모를 줄이는 적극적인 방식이다. 본 논문에서는 무선 센서 네트워크의 클러스터 기반 라우팅 프로토콜인 LEACH(Low-Energy Adaptive Clustering Hierarchy)에 파워 컨트롤 기법을 적용한 LEACH-PC(LEACH-Power Control)를 제안하였다. LEACH-PC는 클러스터 구성에 사용한 RSSI(Received Signal Strength Indicator) 정보를 이용하여 클러스터 내부 통신 단계에서 파워 컨트롤을 수행한다. LEACH-PC는 에너지 효율성 측면에서 기존의 LEACH 보다 좋은 성능을 보임을 실험을 통해 확인할 수 있었다.

• Journal of Drive and Control
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• v.11 no.2
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• pp.9-15
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• 2014

This paper deals with the issue of force synchronizing control for the clamping servomechanism of injection molding machines. Prior to the controller design, a virtual design model has been developed for the clamping mechanism with hydraulic systems. Then, a synchronizing controller is designed and combined with an adaptive feedforward control in order to accommodate the mismatches between the real plant and the linear model plant used. As a disturbance, the leakage due to the ring gap with relative motion in the cylinder has been introduced. From the robust force tracking simulations, it is shown that a significant reduction in the force synchronizing error is achieved through the use of a proposed control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.132.4-132
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• 2001

Field robot represented by excavator can be applied for various kinds of working in manufacturing, construction, agriculture etc. because of the flexibility of its multi-joint mechanism and the high power of hydraulic actuators. In general, the dynamics of field robot have strong coupling, various kinds of non-linearity, and time varying parameters according to working conditions. Therefore, it is very difficult to describe the system well, and design controller systematically based on its model. This paper established the mathematical model of field robot driven by electro-hydraulic servomechanism and constructed the adaptive control system robust to external load variations. The proposed control system for the field robot was evaluated by the computer simulation, and the performance results of trajectory tracking were compared with that of PID control system.