• Proceedings of the KIEE Conference
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• 2000.11a
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• pp.33-35
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• 2000

We propose a intelligent controller for FACTS(Flexible AC Transmission System) device to stabilize a power system. In order to identify the nonlinear characteristics of the power system and to estimate a control signal, an artificial neural network is utilized. The control signal which is provided for FACTS device installed in the network is produced. The proposed controller is applied to Unified Power Flow Controller(UPFC) to verified the effectiveness of the proposed control system. The results show that the proposed nonlinear FACTS controller is able to enhance the transient stability of three machine nine bus power system.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.286-291
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• 1991

This paper discusses sliding made control of robot manipurators assuming that nonlinear terms, which are inertia term, Coriolis force term and centrifugal taffn, are external disturbances. We obtained the unknown parameter of its linear terms by Signal Compression Method. We propose a new control input algorithm to decrease chattering in the application of sliding mode control of manipulator whose nonlinear components are regarded as disturbances. In this experiments, we used DSP(Digital Signal Processor) controller to suppress chattering by obtaining a quick switching speed.

• Journal of Navigation and Port Research
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• v.28 no.4
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• pp.305-309
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• 2004

The problem for parameters estimation of the received signals impinging on array sensors has long been of great research Interest in a great variety of applications, such as radar, sonar, and land mobile communications systems. Conventional subspace-based algorithms, such as MUSIC and ESPRIT, require an extensive computation of inverse matrix and eigen-decomposition In this paper, we propose a new parameters estimation algorithm via nonlinear minimization, which is simplified computationally and estimates signal parameters simultaneously.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.447-450
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• 1990

Nonlinear protection of overcurrent induced on parallel two-wire transmission line by electromagnetic pulse is analyzed. This algorithm is implemented numerically and simulation result for simple incident pulse and nonlinear type agrees with its analytic solution.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.462-462
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• 2000

In this paper, genetic algorithm (GA) is the technique to search for the optimal structures (i,e., the kind of neural network, the number of hidden neuron, ..) of the neural networks which are used approximating a given nonlinear function, In this paper, we used multi layer feed-forward neural network. The decision method of synapse weights of each neuron in each generation used back-propagation method. In this study, we simulated nonlinear function approximation in the temperature control system.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2146-2148
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• 2002

In this paper, PID control method using genetic algorithm to control the nonlinear multivariable system is presented. Genetic algorithms are global search techniques for nonlinear optimization. For experiment, the x-y rod balancing system with driver circuit board is fabricated. Experiments such as angle and position control for system are performed. The validity and control performance of the GA-based PID controller are confirmed by experimental results.

• Bulletin of the Society of Naval Architects of Korea
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• v.23 no.3
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• pp.39-44
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• 1986

The basic BFGS procedure for the nonlinear finite element analysis is reviewed. Through a simple numerical example, promising characteristics of the method evaluated discussed. Based on the discussion of computational performance, a modified BFGS algorithm with substructuring is derived and proposed for the quasi-static analysis of large-scale nonlinear structures.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.368-373
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• 1998

This paper presents a GA-based fuzzy modelling scheme of nonlinear systems. The fuzzy model is a type of the Sugeno-Tagaki's fuzzy model whose consequence parts are described by a linear continuous dynamic equation as subsystem of a nonlinear system. The centers and width of the membership functions of the fuzzy sets defined over the input space and the orders and parameters of subsystems in the consequence parts are adjusted by a genetic algorithm. The effectiveness of the proposed method is verified

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.11
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• pp.922-933
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• 1989

This paper deals with an indirect pole placement adaptive controller design problem for discrete-time plants with arbitrary zeros in the presence of unmodeled dynamics and/or disturbances. The plant and controller parameters are estimated by separate estimators. The nonlinear feedback is introduced so that the estimated plant has as high degree of controllability as possible. The nonlinear feedback will be used in a finite time, after which the control algorithm becomes a standard pole placement one.

• Journal of the Korean Mathematical Society
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• v.44 no.4
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• pp.823-834
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• 2007

We introduce a new system of generalized nonlinear mixed quasivariational inequalities and prove the existence and uniqueness of the solution for the system in Hilbert spaces. The main result of this paper is an extension and improvement of the well-known corresponding results in Kim-Kim [16], Noor [21]-[23] and Verma [24]-[26].