• Smart Structures and Systems
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• 제11권3호
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• pp.315-329
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• 2013

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

• 제어로봇시스템학회논문지
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• 제10권8호
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• pp.734-741
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• 2004

This paper presents a network based fire detection system using CAN, in order to evaluate feasibility of home automation protocol for smart home. In general, because a traditional fire detection system has an analog transmission method with 4-20mA current, it has several shortcomings such as weakness to noise. Hence, as an alternative to the traditional system, this paper presents the architecture of CAN based fire detection system and the design method of CAN communication network. Also, the performance of the suggested system is evaluated through an experimental testbed. Especially, CAN has several advantages such as low cost and easiness of implementation compared to Ethernet or ARCNET, which are low layer of BACNet. Therefore, if CAN is adopted as low layer of BACNet, the home automation system is implemented more effectively.

• 센서학회지
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• 제28권1호
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• pp.64-70
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• 2019

Wireless sensors have been developed in numerous ways for enhancing the convenience of installation, management and maintenance of sensors. Energy harvesting wireless sensors, which can collect energy from the external environment for permanent usage without the need of recharging and exchanging batteries, have been developed and employed used in Internet of Things and at various industrial sites. Energy harvesting wireless sensors are significantly affected by the sensor lifespan to sudden variation in the external environment. Furthermore, reduction in the sensor operating timespan can greatly affect the characteristics of the devices connected through a network. In this paper, a system performance index is proposed that can comprehensively evaluate the lifespan of a solar cell wireless sensor, determine the characteristics of devices connected to the associated network, and recommend dynamic power distribution control for improving the system performance index. Improvement in the system performance index was verified by applying the proposed dynamic power distribution control to an air conditioner network system using a solar cell wireless sensor. Obtained results corroborate that the dynamic power distribution control can extend the lifespan of the incorporated wireless sensor and reduce the air conditioner's power consumption.

• International Journal of Precision Engineering and Manufacturing
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• 제3권3호
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• pp.12-20
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• 2002

As numerous sensors and actuators are used in many automated systems, various industrial networks are adopted for real-time distributed control. In order to take advantages of the networking, however, the network implementation should be carefully designed to satisfy real-time requirements considering network induced delays. This paper presents an implementation scheme of a networked control system via Profibus-DP network fur real-time distributed control. More specifically, the effect of the network induced delay on the control performance is evaluated on a Profibus-DP testbed. Also, two conventional PID gain tuning methods are slightly modified fur fouling controllers fur the networked control system. With appropriate choices for gains, it is shown that the networked control system can perform almost as well as the traditional control system.

• 한국산학기술학회논문지
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• 제10권11호
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• pp.3193-3199
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• 2009

본 실시간 지능형 홈 네트워크 제어시스템은 여러 모바일 기기를 이용하여 통신이 가능한 곳이면 언제 어디서든지 실시간으로 시스템 제어와 모니터링이 가능한 시스템이다. 본 논문은 실시간 지능형 홈 네트워크 제어시스템을 구현하기 위하여 무선 홈 네트워크 기술 중 ZigBee 기술을 이용하여 각종 USN 센서를 제어하는 서버 모듈 구현과 모바일 기기에 탑재되어 사용자에 의해 구동되는 클라이언트 모듈을 GUI환경으로 구성하여 설계 및 구현하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.313-318
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• 1994

It is well known that the neural network can be used as an universal approximater for functions and functionals. But these theoretical results are just an existence theorem and do not lead to decide the suitable network structure. This doubfulness whether a certain network can approximate a given function or not, brings about serious stability problems when it is used to identify a system. To overcome the stability problem, We suggest successive identification and control scheme with supervisory controller which always assures the identification process within a basin of attraction of one stable equilibrium point regardless of fittness of the network.

• 전기학회논문지P
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• 제52권3호
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• pp.95-99
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• 2003

In this paper, the power system automation based on CAN communication protocol is introduced. Along with digitalization of electrical device, the various on-line services such as remote control, remote monitoring, remote parameter setting, fault data recording and remote diagnostic have been realized and become available. Therefore, it is necessary for those electrical devices to have real-time and reliable communication protocols. Author proposes DNPC(Distributed Network Protocol with CAN) which is proper to the power system SCADA (Supervisory Control And Data Acquisition) and DCS (Distributed Control System). The physical and datalink layer of DNPC protocol consists of the CAN2.0B which has the real-time characteristics and powerful error control scheme. As the transport and application layer, DNP3.0 is adopted because of its flexibility and compatible feature. Using the DNPC protocol, the power system automation is realized.

• 융합신호처리학회논문지
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• 제3권3호
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• pp.54-62
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• 2002

본 논문에서는 최근 급속히 진전되고 있는 자동차의 각종 전기신호와 센서 입·출력의 통합제어를 위한 CAN 통신 시스템의 개발에 관해서 기술한다. 본 논문에서 제시하는 CAN 통신을 사용한 통합제어 시스템은 기존의 Wiring Harness (W/H)에 의한 제어기 구성의 문제점인 낮은 신뢰성과 시스템 구성의 비효율성을 개선할 수 있고, 다중화 네트워크에 의한 유니트별 독립적인 제어가 가능함으로 성능향상과 기능확대에 유연하게 대응할 수 있는 특징을 갖는다. 제안 시스템은 성능향상과 함께 높은 신뢰성으로 센서 입·출력의 각종 기능을 통합해서 자동차 신호를 제어 할 수 있는 새로운 통합 시스템의 하나이다. 제안 시스템의 성능을 확인하기 위해, 관련 하드웨어와 프로그램을 개발하고 실제 시스템을 구현해서 그 효율성을 입증한다. 이를 위해 CAN 통신 프로토콜의 특징을 간단히 기술하고, 이를 이용한 차량의 각종 전기신호와 센서들의 통합제어를 수행하는 개발된 하드웨어와 프로그램을 제시한다. CAN 통신의 높은 신뢰성과 각종 신호의 효율적인 제어가 가능함으로 제안된 시스템은 향후 자동 전자제어화에 중요한 모듈이 될 것이다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.14-19
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• 1993

In this paper, we proposed an indirect learning and direct adaptive control schemes using neural networks, i.e., composite adaptive neural control, for a class of continuous nonlinear systems. With the indirect learning method, the neural network learns the nonlinear basis of the system inverse dynamics by a modified backpropagation learning rule. The basis spans the local vector space of inverse dynamics with the direct adaptation method when the indirect learning result is within a prescribed error tolerance, as such this method is closely related to the adaptive control methods. Also hash addressing technique, similar to the CMAC functional architecture, is introduced for partitioning network hidden nodes according to the system states, so global neuro control properties can be organized by the local ones. For uniform stability, the sliding mode control is introduced when the neural network has not sufficiently learned the system dynamics. With proper assumptions on the controlled system, global stability and tracking error convergence proof can be given. The performance of the proposed control scheme is demonstrated with the simulation results of a nonlinear system.

• Journal of Information Processing Systems
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• 제18권6호
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• pp.755-762
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• 2022

The existing electrical engineering design method and the dynamic objective function in the application process of automatic control system fail to meet the unbounded condition, which affects the control tracking accuracy. In order to improve the tracking control accuracy, this paper studies the electrical engineering design method based on neural network and the application of automatic control system. This paper analyzes the structure and working mechanism of electrical engineering automation control system by an automation control model with main control objectives. Following the analysis, an optimal solution of controllability design and fault-tolerant control is figured out. The automatic control power coefficient is distributed based on an ideal control effect of system. According to the distribution results, an automatic control algorithm is based on neural network for accurate control. The experimental results show that the electrical automation control method based on neural network can significantly reduce the control following error to 3.62%, improve the accuracy of the electrical automation tracking control, thus meeting the actual production needs of electrical engineering automation control system.