• 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 D
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• v.53 no.11
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• pp.741-746
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• 2004

When investigating a control problem for network based control systems, the main issue is network-induced delay. This delay can degrade the performance of control systems designed without considering the delay and even destabilize the system. In this paper, we consider the stabilization of network based control systems, where there is bounded time-varying delay. This delay is treated like parameter variation of a discrete time system. The state feedback controller design is formulated as linear matrix inequality. Finally, we show that the stability of control systems designed with considering the delay is superior to that is not so.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.119.3-119
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• 2001

When building a network-based real-time control system, a network-induced delay time should be surly considered for real time schedulability to be guaranteed. The network delay time on end-to-end communication has been analyzed theoretically and modeled mathematically from many previous works. There also exist any other delay element not considered before. In this paper, the remote feedback control system using the CAN protocol is proposed to control three axes´ manipulator arm and the application layer of CAN is modeled to analyze the delay elements defined by three types of time delay: Software delay time, Controller delay time, and Access delay time, in details. The analyzed results are used as an important component to determine PID gains of the proposed system. The effect of the delay time on the control performance is evaluated by com paring the response characteristics of the control system through simulation.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.120-129
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• 2001

As many 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 delays. This paper presents the implementation of a remote feedback control system via Profibus-DP net work for real-time distributed control More specifically, the effect of the network delay on the control performance evaluated on Profibus-DP testbed. Also, the traditional PID gain tuning methods are used to demonstrate the feasibility of the remote feedback control.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1162-1167
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• 2004

This paper presents the design methodology of digital fuzzy controller(DFC) for the systems with time-delay. We propose the fuzzy feedback controller whose output is delayed with unit sampling period and predicted. The analysis and the design problem considering time-delay become easy because the proposed controller is syncronized with the sampling time. The stabilization problem of the digital fuzzy system with time-delay is solved by linear matrix inequality(LMI) theory. Convex optimization techniques are utilized to solve the stable feedback gains and a common Lyapunov function for designed fuzzy control system. To show the effectiveness the proposed control scheme, the network control example is presented.

• Journal of IKEEE
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• v.20 no.4
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• pp.378-384
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• 2016

This paper addresses the output feedback consensus problem for high-order integrators under a directed network with a communication delay. In order to solve this problem, the dynamic output feedback controller is proposed. Also, by using Lyapunov-Krasovskii functional, it is shown that the existence of the proposed consensus controller can always be guaranteed even in the presence of an arbitrarily large communication delay.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2445-2447
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• 2002

In this paper, CAN-based feedback control system is proposed for the pressurization system of korean high-speed train. The control performance of the system is evaluated. According to the requirement of the pressurization system A process model considering network delay and an adaptive PID control method based on the process model are proposed here. And it is shown that the proposed adaptive PID control method considering the network delay has on adequate feature compared to some other existing methods consequently it can be considered to be applied the pressurization system of korean high-speed train.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.446-449
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• 1997

We propose a control law in discrete time domain of the bilateral feedback teleoperation system using neural network and the reference model type of adaptive control. Different from traditional teleoperation systems, the transmission time delay irregularly changes. The proposed control method controls master and slave systems through identification of master and slave models using neural networks.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.491-494
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• 2006

Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.186-189
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• 1996

In most of the recent research literature, network performance is expressed in terms of network engineering measures such as delay or loss. These performance measures are important to network owners and operators, but it is believed that user preferences should be the primary consideration which drives the resource allocation scheme. A network is only as valuable as its users perceive it to be. Therefore, it is advocated that the users themselves determine relative traffic priorities. This paper describes the role of feedback in network resource allocation, which could be part of a user-oriented framework for network operation and control. Feedback mechanism can also be used to improve the two types of efficiency in the network; network efficiency and economic efficiency.