• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.1-9
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• 1996

A key issue in spoken language processing has become the integration of speech understanding and natural language processing(NLP). This paper presents a parallel computational model for the integration of speech and NLP. The model adopts a hierarchically-structured knowledge base and memory-based parsing techniques. Processing is carried out by passing multiple markers in parallel through the knowledge base. Speech-specific problems such as insertion, deletion, and substitution have been analyzed and their parallel solutions are provided. The complete system has been implemented on the Semantic Network Array Processor(SNAP) and is operational. Results show an 80% sentence recognition rate for the Air Traffic Control domain. Moreover, a 15-fold speed-up can be obtained over an identical sequential implementation with an increasing speed advantage as the size of the knowledge base grows.

• Proceedings of the Korean Nuclear Society Conference
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• 2005.05a
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• pp.745-746
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• 2005

• Proceedings of the Korean Nuclear Society Conference
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• 2005.05a
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• pp.747-748
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• 2005

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.215-218
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• 2001

To improve the performance of PID controller of high order systems by model reduction, we proposed a new model reduction method in frequency domain. A new model reduction method we proposed, considered four points (${\angle}G(jw)=0$, $-{\pi}/2$, $-{\pi}$, $-3{\pi}/2$) in stead of two points (${\angle}G(jw)=-{\pi}/2$, and $-{\pi}$) in Nyquist curve. And for high order systems that it have not two point (${\angle}G(jw)=-{\pi}/2$, and $-{\pi}$) in Nyquist curve, we proposed a method to annex very small dead time. This method has a annexed very small dead time on the base model for reduction, and we cancel it after to get the reduced model. It is shown that the performance of proposed method is better than any other methods.

• The Journal of Information Technology
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• v.4 no.2
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• pp.117-127
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• 2001

A self-structured neural network algorithm that finds optimal fuzzy membership functions and nile base to fuzzy model is proposed and a fuzzy-neural network controller is designed to get more accurate position and velocity control of wheeled mobile robot. This procedure that is composed of three steps has its own unique process at each step. The elements of output term set are increased at first step and then the rule base Is varied according to increase of the elements. The adjusted controller is in competition with controller which doesn't include any increased elements. The adjusted controller will be removed if the control-law lost. Otherwise, the controller is replaced with the adjusted system. After finished regulation of output term set and rule base, searching for input membership functions is processed with constraints and fine tuning of output membership functions is done.

• Journal of the military operations research society of Korea
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• v.6 no.1
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• pp.93-101
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• 1980

An effectively designed budget system in the poor resources environment necessarily has three design criteria : (i) to be both planning-oriented and control-oriented, (ii) to be both rationalistic and realistic, (iii) to be sensitive to the variations of resources environment. PPB system is an extreme (planning-oriented and rationalistic) and conventional OEB/OUB system is the other extreme (control-oriented and incrementalistic). Generally, the merits of rationalism are limited because of the infeasibility of applications. Hence, mixtures of the two extremes such as MBO, ZBB, and RZBB have been examined and applied during the last decade. The classical mathematical models of capital budgeting are the starting points of the development of the Budget-Mix Model introduced in this paper. They are modified by the followings: (i) technological-resource constraints, (ii) bounded-variable constraint, (iii) the exchange rules. Special emphasis is laid on the above (iii), because we need more efficient interresource exchanges in the budget-mix process. The Budget-Mix Model is not based on optimization, but a heuristic approach which assures a satisficing solution. And the application fields of this model range between the incremental Nonzero-Base Budgeting and the rational Zero-Base Budgeting. In this thesis, the author suggests 'the budget- mix concept' and a budget-mix model. Budget-mix is a decision process of making program-mix and resource-mix together. For keeping this concept in the existing organization realistic, we need the development of quantitative models describing budget-mix situations.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.128-135
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• 1999

A driving simulators of aircraft and vehicle may consist of hydraulic power systems with many single-rod cylinders. The single-rod hydraulic systems are convenient but need more robust control scheme in order to achieve a reliable performance against the wide range of operating disturbances and the inherent model uncertainties. $H_{\infty}$ control scheme was implemented to the 2 degree-of-freedom hydraulic device similar to the simple driving simulator. With the reasonable disturbances from sensor, base and pump and also with the linearization of model, the simulation and experimental results showed good agreements.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1068-1071
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• 1993

An algorithm of fuzzy predictive sliding control is proposed to design a jet engine control system. Sliding control using predictive scheme is adopted to compensate the time delay of fuel injector. Fuzzy rule-base is also introduced to adjust the command input for suppressing the surge. The potential of the proposed algorithm is shown through simulations utilizing a typical engine-only model.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.133-134
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• 2007

A swing-up control strategy is suggested for a rotary inverted pendulum with restricted rotation range. In order to take the rotation range limitation into account, a new Lyapunov function used for energy-based control is proposed a control strategy is derived from the Lyapunov function. Futhermore, optimization-base parameter estimation is adopted to get an exact mathematical model for the pendulum. Simulation results show that the proposed control strategy swings up the rotary inverted pendulum efficiently.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.22-29
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• 2003

A piezoelectric actuator yields hysteresis effect due to its composed ferroelectric. Hysteresis nonlinearty is neglected when a piezoelectric actuator moves with short stroke. However when it moves with long stroke and high frequency, the hysteresis nonlinearty can not be neglected. The hysteresis nonlinearty of piezoelectric actuator degrades the control performance in precision position control. In this paper, in order to improve the control performance of piezoelectric actuator, an inverse modeling scheme is proposed to compensate the hysteresis nonlinearty. And feedforward - feedback controller is proposed to give a good tracking performance. The Feedforward controller is an inverse hysteresis model, base on neural network and the feedback control is implemented with PID control. To show the feasibility of the proposed controller and hysteresis modeling, some experiments have been carried out. It is concluded that the proposed control scheme gives good tracking performance.