• Journal of Advanced Marine Engineering and Technology
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• v.19 no.3
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• pp.77-83
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• 1995

Recently, in the field of industrial servo-systems, several methods have been proposed for tracking the reference input fastly and finely without overshoot. These methods, however, are established under hypothesis that structure and parameters of the plant are known accurately and they are time invariant. In practice, it is difficult to obtain the values of plant's parameters accurately and usually plants change with time and operation conditions. In this paper a method to construct the nominal model tracking adaptive control system is proposed. The system is composed of the nomial model which produces a ideal response and the model tracking system with the fuzzy adaptive controller. If the actual plant is equal to the controlled object in the nominal model, the output of the plant is the same as that of the nominal model and the fuzzy adaptive controller becomes idle. However, when the plant changes, the fuzzy adaptive controller of the tracking system operates in order for the output of the plant to track the ideal response. Through the computer simulations under various conditions, it is confirmed that the proposed model tracking system is very effective.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.270-275
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• 2005

This paper presents a fuzzy model-based adaptive approach for synchronization of chaotic systems which consist of the drive and response systems. Takagi-Sugeno (T-S) fuzzy model is employed to represent the chaotic drive and response systems. Since the parameters of the drive system are assumed unknown, we design the response system that estimates the parameters of the drive system by adaptive strategy. The adaptive law is derived to estimate the unknown parameters and its stability is guaranteed by Lyapunov stability theory. In addition, the controller in the response system contains two parts: one part that can stabilize the synchronization error dynamics and the other part that estimates the unknown parameters. Numerical examples, including Doffing oscillator and Lorenz attractor, are given to demonstrate the validity of the proposed adaptive synchronization approach.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.7
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• pp.791-799
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• 2006

The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.3
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• pp.31-38
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• 2010

In this paper, we have analyzed and compared the BER and the throughput performance through the computer simulation, after applying several MIMO schemes on the MIMO-OFDM system. Then, the throughput performance of the proposed system, Adaptive-MCM, is analyzed. As a result, the MIMO-OFDM Adaptive-MCM system proposed has a higher average data rate than Non Adaptive-MCM system through the improvement of Trade-off problem between throughput and SNR.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.532-538
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• 1998

In this paper, a new adaptive fuzzy inference method using neural network based fuzzy reasoning is proposed to make a fuzzy logic control system more adaptive and more effective. In most cases, the design of a fuzzy inference system rely on the method in which an expert or a skilled human operator would operate in that special domain. However, if he has not expert knowledge for any nonlinear environment, it is difficult to control in order to optimize. Thus, using the proposed adaptive structure for the fuzzy reasoning system can controled more adaptive and more effective in nonlinear environment for changing input membership functions and output membership functions. The proposed fuzzy inference algorithm is called adaptive neuro-fuzzy control(ANFC). ANFC can adapt a proper membership function for nonlinear plant, based upon a minimum number of rules and an initial approximate membership function. Nonlinear function approximation and rotary inverted pendulum control system ar employed to demonstrate the viability of the proposed ANFC.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.2
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• pp.38-44
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• 1994

Control Algorithms of the Auto-Pilot system have been studied for the navigational economics and crew's comfortability since 1960's, when Auto-Pilot system was installed on the trans-ocean ships. At the beginning the PD control algorithm was used with the weather adjust function introduced to reduce the response of the auto-pilot system to the high frequency wave excitation in rough sea. In this study, the optimal and adaptive control theories are applied for the auto-pilot control algorithm. And those two algorithms are compared through the pre-defined cost function to obtain the most effective control technique for the Auto-Pilot system. The parameterization of the ship meneuvering equation for the adaptive control algorithm design procedure was examined and the advantage of the adaptive control was found through the simulation result with the wrong initial parameter value.

• The Journal of Korean Association of Computer Education
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• v.8 no.4
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• pp.107-114
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• 2005

While a user is using an adaptive hypermedia system, the user can also use an external application. If the user accesses the information which is related to the contents provided by the adaptive hypermedia system, it can affect a user profile that contains the information about the knowledge or interests of the user. However, the adaptive hypermedia system understands user's behavior based on whether a page is accessed or not and it is difficult for the system to recognize user's behavior that can occur outside the adaptive hypermedia system. In this paper, we propose an approach that can detect user's behavior using a message hooking mechanism so that both user's behavior inside an adaptive hypermedia system and behaviors that occur outside the system can be reflected in a user profile. We analyze user events using a hooking mechanism and update a user profile using an XML parser.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1221-1224
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• 1996

As in most industrial processes, the dynamic characteristics of an electric power system are subject to changes. Amongst those effects which cause the system to be uncertain, faults on transmission lines are considered. For the stabilization of the power system, we present an indirect adaptive control method, which is capable of tracking a sudden change in the effective reactance of a transmission line. As the plant dynamics are nonlinear, an input-output feedback linearization method is combined with an identification algorithm which estimates the effect of a fault.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.255-260
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• 1988

A robust adaptive control method for a stable nonminimum phase SISO system with unmodelled dynamics is proposed. The robust parameter estimation method of the system with bounded output noise and unmodelled dynamics is employed and a parallel structure is proposed to improve the robustness of adaptive control system. The local stability of the proposed system is shown. Computer simulations are done in order to compare the performance of the proposed structure with the basic structure on various circumstance.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.333-338
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• 1990

Most verification of improvements for adaptive control schemes are. dependent on computer simulations, but these computer simulations have much limitation, because (if complex actual conditions of system. This paper is concerned with the constructions of a thermal process system for experiments with various control schemes. This thermal process system is composed of a water tank, PC-XT, AD/DA converters power supply and thermal sensors. We estimate. the algorithms of pole-assignment adaptive control in the manifold disturbances and environments, changing system dynamics. The system equations for thermal press are included.