• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.479-481
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• 1999

In this paper, We design low-order controller to achieve maximized controller stability margin and controller' Performance. FOPA(Fixed Order Pole Assignment) method is one of the approach to design controller in the parametric uncertain system. But the method to define a Target Polynomial is not explicit1y Known. In this paper, our goal is to find a controller Coefficient, such that performance and $l_2$ stability margin are maximized in the parametric uncertain system. Using Lipatove theorem and CDM(Coefficient Diagram Method), we set target polynomial constraints and design a controller which maximizes $l_2$ stability margin. we show effectiveness of the proposed controller design method by comparing $l_2$ stability many of the desired controller with that of the conventional robust controller.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.2
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• pp.323-338
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• 1994

This paper outlines a framework for performing intelligent sensor validation for a diagnostic expert system while reasoning under uncertainty. The emphasis is on the algorithmic preprocess technique. A companion paper focusses on heuristic post-processing. Sensor validation plays a vital role in the ability of the overall system to correctly detemine the state of a plant monitored by imperfect sensors. Especially, several theoretical developments were made in understanding uncertain sensory data in statistical aspect. Uncertain information in sensory values is represented through probability assignments on three discrete states, "high", "normal", and "low", and additional sensor confidence measures in Algorithmic Sv.Upper and lower warning limits are generated from the historical learning sets, which represents the borderlines for heat rate degradation generated in the Algorithmic SV initiates a historic data base for better reference in future use. All the information generated in the Algorithmic SV initiate a session to differentiate the sensor fault from the process fault and to make an inference on the system performance. This framework for a diagnostic expert system with sensor validation and reasonig under uncertainty applies in HEATXPRT$^{TM}$, a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants.

• Journal of Power System Engineering
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• v.20 no.2
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• pp.58-65
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• 2016

Lately, tugboats are widely used to maneuver vessels by pushing or towing them where tugboats use rope. In order to correctly control the motion of tugboat and towed vessel, the dynamics of the towline would be well identified. In real application environment, the towing rope length changes and the towing load is not constant due to the various sizes of towed vessel. And there are many ropes made by many types of materials. It means that it is not easy to obtain rope dynamics, such that it is too difficult to satisfy the given control purpose by designing control system. Thus real time identification or adaptive control system design method may be a solution. However it is necessary to secure sufficient information about rope dynamics to obtain desirable control performance. In this paper, the authors try to have several rope dynamic models by changing the rope length to consider real application conditions. Among them, a representative model is selected and the others are considered as uncertain models which are considered in control system design. The authors design a robust control to cope with strong uncertain and nonlinear property included in the real plant. The designed control system based on robust control framework is evaluated by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1500-1505
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• 2004

This paper presents the design and control of a small Brushless DC (BLDC) Motor for entertainment robots. In order to control the developed BLDC motor, Adaptive Fuzzy Control (AFC) scheme via Parallel distributed Compensation(PDC) is developed for the multi- input/multi-output plant model represented by the Takagi-Sugeno(TS) model. The alternative AFC scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal. The suggested design technique is applied to the velocity control of a developed small BLDC motor for entertainment robots.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.189-194
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• 1994

Adaptive control systems based upon the command generator tracker(CGT) approach have attracted considerable interest because of the simple structure of its adaptive controller. Some attempts to such improve the adaptive control algorithm, for the sake of the application to broader class of plants, are made. Recently, Su and Sobel(1992) proposed that those schemes can be treated by an unified theory using a metasystem representation with some types of supplementary dynamics. However, in their method, it is difficult to find the dynamic compensator, which is proper and output feedback stabilizable, for the uncertain plant. This paper proposes a new design method of such supplementary dynamics and some parameters of adaptive control system for linear time invariant SISO plants. The method gives a concrete and systematic design method using only a few priori knowledge of the plant.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.984-987
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• 1996

We consider a feedback control system including interval plant where uncertain parameters expressed in the hyperrectangular box X. Here we define the maximum value of the integral of the error(ISE) as the worst performance index(WPI) due to the plant parameter uncertainty. Suppose that the closed loop system retains robust stability and it belongs to type I. Then we show that the WPI occurs only on the exposed edges of Q. In particular, it is also shown that if ISE is a convex function relative to X, the WPI is attained at one of vertices of X. Some examples are given.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.130-135
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• 2007

In this paper, a direct model reference adaptive fuzzy control (MRAFC) scheme is developed for the plant model whose structure is represented by the MIMO Takagi-Sugeno fuzzy model. The MRAFC scheme is proposed to provide asymptotic tracking of a reference signal lot the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee that all signals in the closed-loop system are bounded. In addition, the plant state tracks the state of the reference model asymptotically with time tot any bounded reference input signal.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.401-403
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• 1992

For the control of robotic manipulators with unknown or uncertain dynamics, leaming control schemes are very effective control schemes for repeated trajectory following tasks. In this class of controllers, control techniques using neural networks have been gaining much attention in recent years.. In this note, we discuss the leaming control techniques using neural networks and propose a new model-based control scheme using multilayered neural networks. Three-layerd neural network is used as a feedback controller to compensate the mismatched terms between model plant and real plant. Computer simulations are performed to show the applicability and the limitation of the proposed controller.

• Korean Journal of Plant Taxonomy
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• v.48 no.1
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• pp.1-8
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• 2018

Mankyua chejuense is the only member of the monotypic genus Mankyua (Ophioglossaceae) and is endemic to Jejudo Island, Korea. To determine the precise phylogenetic position of M. chejuense, two cpDNA regions of 42 accessions representing major members of lycophytes are obtained from GenBank and analyzed using three phylogenetic analyses (maximum parsimony, maximum likelihood, and Bayesian inference). In addition, the divergence time is estimated based on a relaxed molecular clock using four fossil calibration points. The phylogenetic position of Mankyua still appears to be uncertain, representing either the earliest diverged lineage within Ophioglossaceae or a sister to the clade containing Ophioglossum and Helminthostachys. The most recent common ancestor of Ophioglossaceae and its sister lineage, Psilotum, was estimated to be 256 Ma, while the earliest divergence of Mankyua was estimated to be 195 Ma in the early Jurassic.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.32-42
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• 2001

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured stated with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, and indirect Model Reference Adaptive Fuzzy control(MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain for slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop systems. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.