• 전기학회논문지P
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• 제53권3호
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• pp.134-141
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• 2004

Recently, neural network techniques are widely used in adaptive and learning control schemes for production systems. However, in general it takes up a lot of time to learn in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult for the PID gains suitably, lots of researches have been reported with respect of turning schemes of PID gains. A neural network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed neural network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accidents.

• 유공압시스템학회논문집
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• 제8권4호
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• pp.17-23
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• 2011

Proportional control solenoid is a type of modulating valve that can continuously control the valve position with magnetic force of solenoid. Recent microcontroller based digital servocontroller for proportional valve is being developed toward the smart valve with additional features such as enhanced control algorithm for finer process and intelligent on-board diagnosis for maintenance. In this paper, development of servocontroller network control with CAN bus which is free from problems of security and network traffic jam is presented. Design of network control system includes modes of communication between master and slave, assignment of 29bit message identifier and message objects, transaction of communication sequence, etc. Monitoring function and control experiments for remote valve through CAN network prove the extended function of smart valve control system.

• 한국안전학회지
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• 제18권3호
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• pp.154-160
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• 2003

원격지에 위치한 분산제어 시스템과 센서 데이터 또는 제어 명령을 주고받을 때에는 불확실한 시간지연이 발생한다. TCP/IP 프로토콜을 이용한 데이터 네트워크와 마찬가지로 데이터 네트워크와 디바이스 네트워크를 결합한 가상 디자이스 네트워크도 불확실한 시간지연이 내재되어 있다. 이러한 시간지연은 분산제어시스템의 성능을 저하시키고 불안전성을 야기하는 원인이 된다. 본 논문에서는 이러한 네트워크상에 내재하는 시간지연을 평가하고 부정적인 효과를 최소화하기 위하여 Smith Predictor를 적용하였다. 제안된 제어 알고리즘은 실시간 서보제어를 통하여 효과를 입증하였으며 가상 디바이스 네트워크 개념에 근거한 분산제어 시스템을 이용하여 실시간 예지보전을 수행할 때 효과가 있음을 제시하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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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.

• 한국에너지공학회:학술대회논문집
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• 한국에너지공학회 1999년도 추계 학술발표회 논문집
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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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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• 제14권5호
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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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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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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• 제어로봇시스템학회 2002년도 ICCAS
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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.

• 드라이브 ㆍ 컨트롤
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• 제19권1호
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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.