• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.204-208
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• 1990

The digital instrumentation and control system for the large scale system like the power plant must have the form of the heirachical structure. Because most large scale system have many control and process signals and it is distributed in the vade region, it is necessary to partition them into several subsystems. Therefore, the role of SCS(Supervisory Control System) having the functions of controlling and monitoring for the status of subsystems is very important. In this paper, new SCS for the effective control of the large scale system is proposed.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.398-402
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• 1987

In the process industries control & organization consist of interconnections on different levels. The process controls that run these industries are a collection of well-defined functions in the form of standard modules interconnected by a communication network. Real-Time(throughput, response time), operator communication, flexibility, back-up and recovery needs have distribute organization of both system hardware and software. Multi-level systems are aften advocated for controlling complex systems, such as, electric, water, oil, gas plants. In practice, these systems encompass computers and person with their various communication requirements and limitations. Hence, Careful mutual adaptation of computer communications and organizational structure is necessary. This paper concentrates on these interactions between process control and organization on the basis of industrial case studies.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.490-490
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• 2000

Parallel genetic algorithms are particularly easy to implement and promise substantial gains in performance. Its basic idea is to keep several subpopulations that are processed by genetic algorithms. Furthermore, a migration mechanism produces a chromosome exchange between subpopulation. In this paper, a new selection method based on non-linear fitness assignment presented. The use of proposed ranking selection permits higher local exploitation search, where the diversity of populations is structure. Experimental results show that the relation between local-global search balance and the probabilities of reaching a desired solution.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.498-498
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• 2000

A study on the robust control of a composite beam with a distributed PVDF sensor and piezo-ceramic actuator is presented in this paper. 1st and 2nd natural frequencies are considered in the modeling, because robust control theory which has robustness to structured uncertainty is adopted to suppress the vibration. If the controllers designed by H$_{\infty}$ theory do not satisfy control performance, it is improved by $\mu$-synthesis method with D-K iteration so that the $\mu$-controller based on the structured singular value satisfies the nominal performance and robust performance. Simulation and experiment were carried out with the designed controller and the verification of the robust control properties was presented by results.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.376-376
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• 2000

Several algorithmic models have been proposed to estimate software cost and other management parameters. In particular, early prediction of completion time is absolutely essential for proper advance planning and a version of the possible ruin of a project. However, estimation is difficult because of its similarity to export judgment approaches and for its potential as an expert assistant in support of human judgment. Especially, the nature of the Norden/Rayleigh curve used by Putnam, renders it unreliable during the initial phases of the project, in projects involving a fast manpower buildup, as is the case with most software projects. Estimating software development effort is more complexity, because of infrastructure software related to target-machines hardware and process characteristics should be considered in software development for DCS (Distributed Control System). In this paper, we propose software development effort estimation technique using adaptive neural fuzzy inference system. The methods is applied to case-based projects and discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.88-88
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• 2000

As more and more critical commercial applications move on the Internet, providing highly available servers becomes increasingly important. One of the advantages of a clustered system is that it has hardware and software redundancy. High availability can be provided by detecting node or daemon failure and reconfiguring the system appropriately so that the workload can be taken over bi the remaining nodes in the cluster. This paper presents how to provide the guaranteeing high availability of clustering web server. The load balancer becomes a single failure point of the whole system. In order to prevent the failure of the load balancer, we setup a backup server using heartbeat, fake, mon, and checkpointing fault-tolerance method. For high availability of file servers in the cluster, we setup coda file system. Coda is a advanced network fault-tolerance distributed file system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.168-168
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• 2000

In this paper, a boiler control system for thermal power plant is configured. The boiler control system for thermal power plant is largely composed of an ABC(Automatic Boiler Control) system and a MBC(Mill Burner Control) system. ABC system controls analog process values, so almost all analog control logic is dealt with in ABC system. On the other hand, MBC system relates to sequence control logic such as MFT logic, Furnace Purge, Safety related logic. Advanced control systems made from advanced countries deal with an ABC system and MBC system in a distributed control system. In this paper, we adopt a DCS as an ABC system and adopt a PLC system as a MBC system to configure a boiler control system for thermal power plant using domestic control system. Finally the validity of the configured boiler control system is shown via simulation using digital simulator for boiler system in thermal power plant.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.624-636
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• 2006

This paper proposes a hybrid approach involving Genetic Algorithm (GA) and Bacterial Foraging (BF) for tuning the PID controller of an AVR. Recently the social foraging behavior of E. coli bacteria has been used to solve optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the life time of the bacteria. Further, the proposed algorithm is used for tuning the PID controller of an AVR. Simulation results are very encouraging and this approach provides us a novel hybrid model based on foraging behavior with a possible new connection between evolutionary forces in social foraging and distributed non-gradient optimization algorithm design for global optimization over noisy surfaces.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.147-150
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• 1998

The report presents basic functions of Time-delay System Toolbox (for MATLAB) -the general-purpose software package for Computer Aided Design of control systems with delays. The Toolbox is a collection of algorithms, expressed mostly in m-files for simulating and analysis of MIMO linear and nonlinear systems with discrete and distributed (time-varying) delays.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.69.2-69
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• 2001

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes.