• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.1
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• pp.21-31
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• 2000

In this paper, an analysis of the stability for a class of discrete-time neural network control systems is presentd. Based on Lyapunov's direct method, a sufficient stability condition for the neural network control systems is systematically derived and the modified back propagation algorithm which reflects the derived stability condition is suggested. The modified BP originates from the derived sufficient condition and guarantees the exponential stability of the resulting trained closed system. Finally, computer simulation is included to show an example where the derived stability condition and the BP modified bythe condition is used to train the control plant.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.96-99
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• 1999

In this paper, a sliding node controller guaranteeing finite time error convergence is proposed jot uncertain systems. By using a novel sliding hyperplane, it is guaranteed that the output tracking error converges to zero in finite time.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2402-2406
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• 2005

A collision query determines the intersection between given objects, and is used in computer-aided design and manufacturing, animation and simulation systems, and physically-based modeling. Bounding volume hierarchies are one of the simplest and most widely used data structures for performing collision detection on complex models. In this paper, we present hierarchy of oriented rounded bounding volume for fast proximity queries. Designing hierarchies of new bounding volumes, we use to combine multiple bounding volume types in a single hierarchy. The new bounding volume corresponds to geometric shape composed of a core primitive shape grown outward by some offset such as the Minkowski sum of rectangular box and a sphere shape. In the experiment of parallel close proximity, a number of benchmarks to measure the performance of the new bounding box and compare to that of other bounding volumes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.267-274
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• 2011

Recently, actor-critic methods have drawn significant interests in the area of reinforcement learning, and several algorithms have been studied along the line of the actor-critic strategy. In this paper, we consider a new type of actor-critic algorithms employing the kernel methods, which have recently shown to be very effective tools in the various fields of machine learning, and have performed investigations on combining the actor-critic strategy together with kernel methods. More specifically, this paper studies actor-critic algorithms utilizing the kernel-based least-squares estimation and policy gradient, and in its critic's part, the study uses a sliding-window-based kernel least-squares method, which leads to a fast and efficient value-function-estimation in a nonparametric setting. The applicability of the considered algorithms is illustrated via a robot locomotion problem and a tunnel ventilation control problem.

• International Journal of Safety
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• v.3 no.1
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• pp.38-46
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• 2004

This paper introduces the software life-cycle V&V (verification and validation) tasks for the KNICS (Korea nuclear instrumentation and control system) project. The objectives of the V&V tasks are mainly to develop a programmable logic controller (PLC) for safety critical instrumentation and control (I&C) systems, and then to apply the PLC to developing the prototype of an engineered safety features-component control system (ESF-CCS) in nuclear power plants. As preparative works for the software V&V, various kinds of software plans and V&V task procedures have been developed according to the software life-cycle management. A number of software V&V tools have been adopted or developed to efficiently support the V&V tasks. The V&V techniques employed in this work include a checklist-based review and inspection, a requirement traceability analysis, formal verification, and life-cycle based software testing.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.259-262
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• 1997

In this paper, a fuzzy model based on the polynomial Neural Network(PNN) structure is proposed to estimate the emission pattern for air pollutant in power plants. The new algorithm uses PNN algorithm based on Group Method of Data Handling (GMDH) algorithm and fuzzy reasoning in order to identify the premise structure and parameter of fuzzy implications rules, and the least square method in order to identify the optimal consequence parameters. Both time series data for the gas furnace and data for the NOx emission process of gas turbine power plants are used for the purpose of evaluating the performance of the fuzzy model. The simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy anhd feasibility than other works achieved previously.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.627-632
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• 2016

In this paper, we propose a new vision-based defect inspection system for the surface of hot slabs. To minimize the influence of self-emission from slab surfaces with high temperature, an optic method based on blue LED light and a blue pass filter is proposed. Because the slab surface is partially covered with scales, which are unavoidable oxidized substances caused during manufacturing, it is difficult to distinguish between vertical cracks and scale. In order to resolve this problem and to improve the detection performance, the use of a Gabor filter and dynamic programming are proposed. Finally, the effectiveness of the proposed method is shown by means of experiments conducted on images of hot slabs that were obtained from an actual slab production line.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.494-496
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• 1999

In this paper, we consider the design of a state feedback $H_{\infty}$ controller for uncertain linear systems with saturating actuators. We consider a general saturating actuator and employ the additive decomposition to deal with it effectively. And the considered uncertainty is the unstructured uncertainty which is only known its norm bound. Based on Linear Matrix Inequality(LMI) techniques, we present a condition on designing a controller that guarantees the $L_2$ gain, from the noise to the output, is not greater than a given value. A controller is obtained by checking the feasibility of three LMI's, and this can be easily done by well-known control package. Finally, we show the usefulness of our result by a numerical example.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.596-598
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• 1999

In this paper, we consider the design of a state feedback $H_{\infty}$ controller for linear systems with saturating actuators. We consider a general saturating actuator and employ the multiplicative decomposition to deal with it effectively. Based on Linear Matrix Inequality (LMI) techniques, we present a condition on designing a controller that guarantees the $L_2$ gain, from the noise to the output, is not greater than a given value. A controller is obtained by checking the feasibility of three LMI's, and this can be easily done by well-known control package. Finally, we show the usefulness of our result by a numerical example.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.323-327
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• 1995

A new air knife system for coating thickness control in hot dip galvanizing process had been developed and installed on the CGL in Pohang Steel Works, POSCO. This new system consists of air knives with remotely adjustable nozzle slot and an automatic control system which can control both longitudinal and traverse coating deviations. Based on the optimal control algorithm, a traverse coating deviation control was designed. The controller controls the lip profile of the air knives with flexible structure according to the deviation of coating weight. From the measured values which are dependent on the strip width, the lip gaps are calculated with optimal algorithm and the model of the coating deviation. Time delay between knives and a coating thickness gauge is solved by the Smith Predictor.