• The KIPS Transactions:PartA
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• 제8A권1호
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• pp.56-62
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• 2001

This paper presents a neural network based variable structure control scheme for nonlinear systems. In this scheme, a set of local variable structure control laws are designed on the basis of the linear models about preselected representative points which cover the range of the system operation of interest. From the combination of the set of local variable structure control laws, neural networks infer the approximate control input in between the operating points. The neural network based variable structure control alleviates the effects of model uncertainties, which cannot be compensated by the control techniques using feedback linearization. It also relaxes the discontinuity in the system’s behavior that appears when the control schemes based on the family of the linear models are applied to nonlinear systems. Simulation results of a ball and beam system, to which feedback linearization cannot be applied, demonstrate the feasibility of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.993-996
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• 1993

This paper addresses the structure and its associated learning algorithms of a feedforward multi-layered connectionist network, which has distributed learning abilities, for realizing the basic elements and functions of a traditional fuzzy logic controller. The proposed neural-network-based fuzzy logic control system (NN-FLCS) can be contrasted with the traditional fuzzy logic control system in their network structure and learning ability. An on-line supervised structure/parameter learning algorithm dynamic learning algorithm can find proper fuzzy logic rules, membership functions, and the size of output fuzzy partitions simultaneously. Next, a Reinforcement Neural-Network-Based Fuzzy Logic Control System (RNN-FLCS) is proposed which consists of two closely integrated Neural-Network-Based Fuzzy Logic Controllers (NN-FLCS) for solving various reinforcement learning problems in fuzzy logic systems. One NN-FLC functions as a fuzzy predictor and the other as a fuzzy controller. As ociated with the proposed RNN-FLCS is the reinforcement structure/parameter learning algorithm which dynamically determines the proper network size, connections, and parameters of the RNN-FLCS through an external reinforcement signal. Furthermore, learning can proceed even in the period without any external reinforcement feedback.

• International Journal of Control, Automation, and Systems
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• 제6권4호
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• pp.596-606
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• 2008

In this paper, we present a co-design methodology of dynamic optimal network-bandwidth allocation (ONBA) and adaptive control for networked control systems (NCSs) to optimize overall control performance and reduce total network-bandwidth usage. The proposed dynamic co-design strategy integrates adaptive feedback control with real-time scheduling. As part of this co-design methodology, a "closed-loop" ONBA algorithm for NCSs with communication constraints is presented. Network-bandwidth is dynamically assigned to each control loop according to the quality of performance (QoP) information of each control loop. As another part of the co-design methodology, a network quality of service (QoS)-adaptive control design approach is also presented. The idea is based on calculating new control values with reference to the network QoS parameters such as time delays and packet losses measured online. Simulation results show that this co-design approach significantly improves overall control performance and utilizes less bandwidth compared to static strategies.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.100-103
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• 1999

In this paper, a method for the efficient implementation of the PICNET network configurator for a distributed control system(DCS) is proposed. The network configurator is composed of the time parameter estimator and the period scheduler, the file generator. The main role of network configurator estimates time parameter, the pre-run time scheduling of the user input and make the period transmission table for operating the PICNET based distributed control system.

• Proceedings of the KIEE Conference
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.106-108
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• 1997

Many new office buildings are being built as intelligent buildings equipped with building automation(HA) systems, office automation(OA) systems, and telecommunication(TC) systems in order to provide pleasant building environment and the ease of maintenance and facility management. Building control systems which are employed in intelligent buildings require varieties of advanced control systems and network systems for efficient integrated management. Design and installation of these types of advanced building control systems take a lot of efforts and also they are costly. In order to design these systems, it is necessary for the designers to have the integrated simulator including proper network system simulation. In this paper, the integrated simulator that consist of HVAC system, lighting system, elevator system, parking system based on the network system is presented. For the development of integrated simulator, AHENA which is the general-purpose software tool for a simulation with reinforced GUI is used.

• Journal of Institute of Control, Robotics and Systems
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• 제6권4호
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• pp.313-319
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• 2000

As the interest of flexible manufacturing systems and computer integrated manufacturing systems increase, the distribution of centralized control systems using industrial control networks is getting more attention. In this paper, we investigate the rate-based traffic control of industrial control networks to improve the performance regarding the throughput, fairness, and error rates. Especially, we consider the protocol of Lon-$Works^{(TM)}$ which consists of all OSI 7-layers and supports various communication media at a low cost. Basically, the proposed rate-based traffic control system is closed loop by utilizing the feedback channel errors, which shows improved performance when compared with other industrial control networks commonly operated in open loop. To this end, an additional network node called monitoring node is introduced to check the channel status without increasing the channel load. The Proposed control loop is in effect whenever the feedback channel error becomes greater than an admittable value. We demonstrate the improved performance of the controlled network system in view of throughput and fairness measures by implementing the lab-scale network system based on LonWorks and through the experimentation upon it.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1581-1585
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• 2005

This paper describes the design and implementation of a XCP (Xeline Control Protocol) network system. XCP is an information oriented protocol which delivers information with high reliability according to the predefined rule. The XCP network system is implemented with partly hardware and partly software based on the power line communication(PLC) environment. A network management tool which interacts with devices is also developed. In order to verify the feasibility of the proposed architecture, the implemented XCP network system is evaluated using a lighting control system.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1598-1601
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• 2005

In this paper, a heterogeneous home network control system using HNCP is proposed and implemented. A power line and 802.15.4 are used as media for the system. Information about home environment gathered by sensors is transferred to a power line connected device through the 802.15.4. HNCP stimulate the home network based on the both media. Sensor device definition for the HNCP address and message set is proposed. TinyOS supports the HNCP stack on the wireless sensor board. The home network control system implemented with these techniques has a benefit of user friendly operation of home appliances based on the sensing data. Implementation and experiment shows validity of the system.

• International Journal of Control, Automation, and Systems
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• 제5권5호
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• pp.515-525
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• 2007

In this paper, we develop a co-design methodology of stochastic optimal controllers and network parameters that optimizes the overall quality of control (QoC) in networked control systems (NCSs). A new dynamic model for NCSs is provided. The relationship between the system stability and performance and the sampling frequency is investigated, and the analysis of co-design of control and network parameters is presented to determine the working range of the sampling frequency in an NCS. This optimal sampling frequency range is derived based on the system dynamics and the network characteristics such as data rate, time-delay upper bound, data-packet size, and device processing time. With the optimal sampling frequency, stochastic optimal controllers are designed to improve the overall QoC in an NCS. This co-design methodology is a useful rule of thumb to choose the network and control parameters for NCS implementation. The feasibility and effectiveness of this co-design methodology is verified experimentally by our NCS test bed, a ball magnetic-levitation (maglev) system.