• Journal of the Korean Society of Safety
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• v.18 no.3
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• pp.154-160
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• 2003

Uncertain time delay happens when the process reads the sensor data and sends the control input to the plant located at a remote site in distributed control system. As in the case of data network using TCP/IP, VDN that integrates both device network and data network has uncertain time delay. Uncertain time delay can cause degradation in performance and stability of distributed control system based on VDN. This paper first investigates the transmission characteristic of VDN and suggests a control scheme based on the Smith's predictor to minimize the effect of uncertain varying time delay. The validity of the proposed control scheme is demonstrated with real-time velocity control of DC servo motor located in remote site.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2419-2422
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• 2000

A distributed real-time system that is being used now is usually divided into three level : higher level, middle level, and lower level. The higher level network is usually called an information network, the middle level is called a control network, and the lower level is called a field network or a divice network. This dissertation suggests and implements a middle level network which is called PICNET-NP (Plant Implementation and Control Network for Nuclear Power Plant). PICNET-NP is based partly on IEEE 802.4 token-passing bus access methed and partly on IEEE 802.3 physical layer. For this purpose a new interface, a physical layer service translater, is introduced. A control network using this method is implemented and applied to a distributed real-time system.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1999.11a
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• pp.143-148
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• 1999

A distributed real-time system that is being wed now is usually divided into three level : higher level, middle level, and lower level. The higher level network is usually called an information network, the middle level is called a control network, and the lower level is called a field network or a divice network. This dissertation suggests and implements a middle level network which is called PICNET-NP (Plant Implementation and Control Network for Nuclear Power Plant). PICNET-NP is based partly on IEEE 802.4 token-passing bus access method and partly on IEEE 802.3 physical layer. For this purpose a new interface, a physical layer service translator, is introduced. A control network using this method is implemented and applied to a distributed real-time system.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.472-474
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• 1998

We study the transient stability control problem for electric power system. Passivity-based control method is used to obtain transient stability. We propose a method which uses neural network to obtain passivity and the transient stability, and compare the simulation result with that of speed gradient method which was developed by other researchers.

• Journal of Power Electronics
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• v.14 no.5
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• pp.980-988
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• 2014

This paper proposes an online gain tuning algorithm for a robust sliding mode speed controller of surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed controller is constructed by a fuzzy neural network control (FNNC) term and a sliding mode control (SMC) term. Based on a fuzzy neural network, the first term is designed to approximate the nonlinear factors while the second term is used to stabilize the system dynamics by employing an online tuning rule. Therefore, unlike conventional speed controllers, the proposed control scheme does not require any knowledge of the system parameters. As a result, it is very robust to system parameter variations. The stability evaluation of the proposed control system is fully described based on the Lyapunov theory and related lemmas. For comparison purposes, a conventional sliding mode control (SMC) scheme is also tested under the same conditions as the proposed control method. It can be seen from the experimental results that the proposed SMC scheme exhibits better control performance (i.e., faster and more robust dynamic behavior, and a smaller steady-state error) than the conventional SMC method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.303-308
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• 2004

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes learning approach of fuzzy-neural network by immune algorithm. The proposed learning model is presented in an immune based fuzzy-neural network (FNN) form which can handle linguistic knowledge by immune algorithm. The learning algorithm of an immune based FNN is composed of two phases. The first phase used to find the initial membership functions of the fuzzy neural network model. In the second phase, a new immune algorithm based optimization is proposed for tuning of membership functions and structure of the proposed model.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.94.3-94
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• 2002

Modern distributed control systems focus on system openness, network system architecture and PC based controller. This paper discusses the embedded systems with ORB for distributed control systems. Embedded systems have merits such as small size, low cost and user convenience. ORB allows users to program easily by using IDL and provides client/server network for heterogeneous platforms. By using embedded systems and ORB, we implement the system and validate it by using VME system. The developed system has benefits when it is applied to distributed control systems.

• Journal of Drive and Control
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• v.19 no.1
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• pp.51-61
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• 2022

This paper presents a model-free system based on a framework of a backstepping sliding mode control (BSMC) with a radial basis function neural network (RBFNN) and adaptive mechanism for electro-hydraulic systems (EHSs). First, an EHS mathematical model was dedicatedly derived to understand the system behavior. Based on the system structure, BSMC was employed to satisfy the output performance. Due to the highly nonlinear characteristics and the presence of parametric uncertainties, a model-free approximator based on an RBFNN was developed to compensate for the EHS dynamics, thus addressing the difficulty in the requirement of system information. Adaptive laws based on the actor-critic neural network (ACNN) were implemented to suppress the existing error in the approximation and satisfy system qualification. The stability of the closed-loop system was theoretically proven by the Lyapunov function. To evaluate the effectiveness of the proposed algorithm, proportional-integrated-derivative (PID) and improved PID with ACNN (ACPID), which are considered two complete model-free methods, and adaptive backstepping sliding mode control, considered an ideal model-based method with the same adaptive laws, were used as two benchmark control strategies in a comparative simulation. The simulated results validated the superiority of the proposed algorithm in achieving nearly the same performance as the ideal adaptive BSMC.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.117-119
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• 2006

BACnet(Building Automation and Control networks) is a standard data communication protocol designed specifically for building automation and control systems. BACnet provides five options for datalink layer protocols and these five datalink layer options can be applied with various transmission media. Recently wireless technology prevails in automation area. ZigBee is a standard protocol based on IEEE 802.15.4 for low-speed wireless communication network. In this study, we propose a BACnet/ZigBee model that uses ZigBee wireless technology in a BACnet communication network system as a wireless datalink layer protocol. We also applied this model to a lighting control system to evaluate the feasibility of proposed technology. The technology proposed in this paper can extend the application of BACnet not only for building automation but also for home automation by taking the advantages of ZigBee wireless communication technology in BACnet communication network systems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.5
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• pp.603-609
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• 2004

This paper deals with the issue of Neural Network-based control for a rodless pneumatic cylinder system which is utilized for a pneumatic XY-plotter. In order to identify the system design parameters, the open loop response of a pneumatic rodless cylinder controlled by a pneumatic servovalve is investigated by applying a self-excited oscillation method. Based on the system design parameters, the PD feedback compensator is designed and then Neural Network is incorporated with it. The experiment of a trajectory tracking control using a PD-NN has been performed and proved its excellent performance by comparing with that of a PD feedback compensator.