• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.11a
• /
• pp.994-998
• /
• 1996

We propose an approach to integrating fuzzy logic control with RBF(Radial Basis Function) networks and show how the integrated network can be applied to multivariable self-organizing and self-learning fuzzy controller. Using the hybrid learning algorithm. To investigate its usefulness and performance, this controller is applied to a time-delayed process system. Simulation results show good control performance and fast convergency in hybrid loaming method.

• Proceedings of the IEEK Conference
• /
• 2002.07c
• /
• pp.1875-1877
• /
• 2002

There exist several forms of transfer function descriptions for multivariable LTI systems. We treat transfer function matrix with characteristic polynomial as its common denominator named Characteristic Transfer-function Matrices (CTM). First, we clarify necessary and sufficient conditions of CTM, then, we show some related lemmas. These interpretations not only offer deeper explanations but they also provide ways for calculations of all possible transfer matrices, system zeros, and inverse polynomial matrices.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1264-1267
• /
• 2005

Fuzzy logic control has been widely applied for handling the system which has uncertainty or high robust system. Since the dynamic behaviors of the systems contain complexity and uncertainty in its parameters, several fuzzy logic controllers have been implemented to control room temperature in the field of air conditioning system. In this paper, the fuzzy logic control has been developed to control both in door temperature and humidity in the air conditioning systems. The manipulating variables are speed of compressor, heater and supply air flow rate. The microcomputer was used to interface with in system. The experimental results show the superior of multivaiable fuzzy logic control to keep room temperature and humidity in air conditioning system for the best comfortable.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.878-883
• /
• 1991

In this paper, we propose the fuzzy-neural controller which is fuzzy controller with learning ability of neural network. The neural network in this controller is same as the membership function in current fuzzy controller and a parts of inference rules. And, it can be easily extend the control algorithm to multivariable systems. We can show effectiveness of the control algorithm through experiment of the inverted pendulum system.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.451-456
• /
• 1990

We treat the problem of the robust tracking of a class of nonlinear systems which can be asymptotically decoupled in approximate sense by state variable feedback. A nonlinear control law is derived such that the tracking error in the closed loop system is uniformly bounded and tends to a certain small neighborhood of the origin. Simulation results show that simultaneous lateral and longitudinal maneuvers in airplane can be accurately performed in spite of uncertainty in stability derivatives.

• Journal of the Korean Society for Precision Engineering
• /
• v.5 no.2
• /
• pp.43-55
• /
• 1988

The control system of a drum boiler is very complex since the evaporization process in the boiler is a multivariable system which is affected one another. This study is concerned with the dynamic characteristics of the boiler process and improving methods of performance of a drum boiler control system. The PID control with feedforward of disturbances and the optimal regulator are compared, and the effects of control parameters on the performance of a boiler control system are investigated. From simulation, it is found that profer adjustment of control parameters significant improvement of response and that performance of a optimal regulated control system is better than that of a conventional PID control system.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.13 no.2
• /
• pp.234-234
• /
• 1999

The aim of this paper is to suggest a design method of the optimal model following control system using genetic algorithm (GA). This control system is designed by applying GA with reference model to the optimal determination of weighting matrices Q, R that are given by LQ regulator problem. The method to do this is that all the diagonal elements of weighting matrices are optimized simultaneously by GA, in the search domain selected adequately. And we design the model following control system to boi1er-turbine equipment by the proposed method. The model following control system designed by this method has the better command tracking performance than that of the control system designed by the trial-and-error method. The effectiveness of this control system is verified by computer simulation.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.5 no.1
• /
• pp.33-42
• /
• 1995

A practical application of a fuzzy-neuro controller is described for an air-conditioning system. Air-handing units are being widely used for improving the performance of central air-conditioning systems. The fuzzy-neuro control system has two controlled variables, temperature and humidity and three control elements, cooling, heating, and humidification. In order to achieve high efficiency and economical contorl, especially in large offices and industrial buildings, two controllable parameters, temperature and humidity, must be adequately controlled by the three final controlling elements. In this paper a fuzzy-neuro control system is described for controlling air-conditioning systems efficiently and economically. Simulation results confirmed that the fuzzy neuro control system is effective for this multivariable system.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.36 no.5
• /
• pp.360-366
• /
• 1987

The design problem of optimal constant PIDM (proportional-integral-derivative and measurable variable) feedback controller for linear time-invariannt systems is investigated with the time-weighted quadratic performance index. Necessary conditions for an optimality of the controller are derived and an algorithm for computing the optimal feedback gain is presented. It is shown via example that the design mithod using the time-weighted quadratic performance index improves the transient responses of the closed-loop system.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.35 no.11
• /
• pp.511-518
• /
• 1986

An algorithm for block-decomposition of a linear, time-invariant, discrete large-scale systems is presented, based upon the matrix sign function on Z-plane. The block-decomposition is performed by defining a reference circle, a circular stripe and projection operators. Simulation study shows that the presented algorithm is very useful for multivariable control system's analysis and design.