• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.695-699
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• 2003

It is general to use the control network in control systems in order to reduce the complexity of the related wiring harnesses and to improve the system flexibility. CAN becomes one of the most popular network protocols because of its low price, multiple sources, high performance and reliability. This paper describes a CAN based real-time control of the fire detection system for the intelligent building system. The proposed fire detection and alarm system is stronger than the previous one against noises and communication media faults and can solve many problems such as complex cabling and increment of I/O ports by using many sensors. Furthermore, MMI can be achieved easily with the personal computer that is used for replacing the traditional monitoring system. The proposed system is implemented and the experimental results are given.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.96.2-96
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• 2001

This paper presents a control method for the experimental mobile vehicle. By merging the advantages of neural network, adaptive and fuzzy control, neural network-based adaptive fuzzy control is proposed. It can deal with a large amount of training data by neural network, from these data producing more accurate fuzzy rules by adaptive control, and then controlling the object by fuzzy control. This is not the simple combination of the three methods, but merging them into one control system Experiments and some future considerations are given.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.47-57
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• 2006

This paper presents a network-based traction control system(TCS), where several electric control units (ECUs) are connected by a controller area network(CAN) communication system. The control system consists of four ECUs: the electricthrottle controller, the transmission controller, the engine controller and the traction controller. In order to validate the traction control algorithm of the network-based TCS and evaluate its performance, a Hardware-In-the-Loop Simulation(HILS) environment was developed. Herein we propose a new concept of the HILS environment called the network-based HILS(Net-HILS) for the development and validation of network-based control systems which include smart sensors or actuators. In this study, we report that we have designed a network-based TCS, validated its algorithm and evaluated its performance using Net-HILS.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.638-651
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• 2000

When the bandwidth resources in a packet-switched network are shared among sessions by MAX-MIN flow control each session is required to transmit its data into the network subject to the MAX-MIN fair rate which is solely determined by network loadings. This passive behavior of sessions if fact can cause seri-ous QoS(Quality of Service) degradation particularly for real-time multimedia sessions such as video since the rate allocated by the network can mismatch with what is demanded by each session for its QoS. In order to alleviate this problem we extend the concept of MAX-MIN fair bandwidth allocations as follows: Individual bandwidth demands are guaranteed if the network can accommodate them and only the residual network band-width is shared in the MAX-MIN fair sense. On the other hand if sum of the individual bandwidth demands exceeds the network capacity the shortage of the bandwidth is shared by all the sessions by reducing each bandwidth guarantee by the MAX-MIN fair division of the shortage. we present a novel flow control algorithm to achieve this extended MAX-MIN fairness and show that this algorithm can be implemented by the existing ATM ABR service protocol with minor changes. We not only analyze the steady state asymptotic stability and convergence rate of the algorithm by appealing to control theories but also verify its practical performance through simulations in a variety of network scenarios.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.58-58
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• 2000

As many sensors and actuators are used in various automated systems, the application of network system to real-time distributed control is gaining acceptance in many industries. In order to take advantages of the network technique. however, network implementation should be carefully designed to satisfy real-time constraints and to consider network delays. This paper presents the implementation of feedback control system in Profibus-DP. Profibus-DP is a type of fieldbus protocols that are specifically designed to interconnect simple devices with fast I/O data exchange. As feedback control in profibus-DP is implemented, Network delays is found with influence of system performance. We analyze network delays in Profibus-DP into 3 reasons - dead time in Profibus interface, protocol delay, delay by asynchronization. In order to compensate the network delays, we introduce control algorithms with time delay concept. The results show that network delay can be compensated.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.78-101
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• 2017

High-quality industrial control is critical to ensuring production quality, reducing production costs, improving management levels and stabilizing equipment and long-term operations. WiFi-based Long Distance (WiLD) networks have been used as remote industrial control networks. Real-time performance is essential to industrial control. However, the original mechanism of WiLD networks does not minimize end-to-end delay and restricts improvement of real-time performance. In this paper, we propose two algorithms to obtain the transmitting/receiving phase cycle length for each node such that real time constraints can be satisfied and phase switching overhead can be minimized. The first algorithm is based on the branch and bound method, which identifies an optimal solution. The second is a fast heuristic algorithm. The experimental results show that the execution time of the algorithm based on branch and bound is less than that of the heuristic algorithm when the network is complex and that the performance of the heuristic algorithm is close to the optimal solution.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.315-318
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• 2005

This paper characterizes the performance for a remote path tracking control of the mobile robot in IP network viamiddleware. The middleware is used to alleviate the effect of the delay time on a mobile robot path tracking in Network-Based Control environment. The middleware also can be implemented in a modular structure. Thus, a controller upgrade or modification for other types of network protocols or different control objectives can be achieved easily. A case study on a mobile robot path-tracking with IP network delays is described. The effectiveness of the proposed approach is verified by experimental results.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2242-2244
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• 2003

This paper considers a networked control system (NCS) that consists of an inverted cart pendulum, a digital controller, and a controller area network (CAN) in which the actuator and sensors of the pendulum are connected to form a closed-loop system. The worst-case message response time (WCMRT) in the CAN is analyzed and the analysis results are applied to the target control system. For the case where the control system cannot satisfy the WCMRT condition and therefore time delays are inevitable, the Luck and Ray method is used to compensate the network-induced time delays. Simulations are carried out to show the feasibility of the proposed scheme.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.39-41
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• 1995

The inherent performance of Ultrasonic Motor(USM) which is on of highlighted a directly-driven positioning servo motor/actuator. In this paper, the speed of control USM based on neural network control. The neural network control can roughly be classified as the direct control and indirect control schemes. An indirect control scheme is adopted for Ultrasonic Motor speed control. A back propagation algorithm is used to train neural network controller. The Simulation results show that this neural network control system can provide good dynamical responses.