• Journal of the Korean Society for Precision Engineering
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• v.13 no.6
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• pp.102-113
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• 1996

An experimental and theoretical study on a pneumatic servo system has been conducted using on-off valves and a pneumatic cylinder. A V/I converter has been designed for rapid rising and falling of the solenoid current, which significantly improves the positioning accuracy and settling time of the servo system by shortening the valve opening time. Pulse width modulation was modified to operate on-off valves effectively. A state feedback controller which feeds back position, velocity and acceleration is used to control the system. The influence of controller gains on the system performance is studied to develop a scheme that automatically adjusts the gains using fuzzy logic theory. It is shown experimentally that the proposed fuzzy logic tuner works satisfactorily. A new method for measurements of valve effective areas is proposed, and a partially polytropic model is applied to simulation of the pneumatic system. Simulated results show good agreement with experimental data.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.685-688
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• 1995

In this paper we proposed new scheme replacing adaptive mechanism part in MRAC by fuzzy logic in order to improve transient response in adaptive control system. Conventional adaptive control system has good performance in steady state but it has large error or problem with rise time in transient state. We need to increase adaptation gain of control variable but it causes robustness problem that makes ststem unstable for set-point, load-variation, and dynamic change. To demonstrate presented FTAC(fuzzy tunning adaptive control)'s superiority, presented method is introduced for a class of SISO systems and compare with MRAC. By analyzing simulation result, we can see transient response is improved and the system is not affected by disturbance in proposed method in comparison to MRAC.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.488-493
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• 2008

A mathematical model of molten steel level for continuous casting process is presented, where the molten steel level, input and output flow in the mold, the relation between stopper position and input flow etc. are considered. The mathematical model is implemented and simulated by using MATLAB. Comparing the result of molten steel level from the simulator with that of real plant, the performance of the model is shown to be reasonable. By using this simulator, it is shown that PI controller with variable P gain, adjusted by fuzzy logic system, has better control result than conventional PI controller.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.779-789
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• 2010

Sport commentators play an increasingly influential role in commercial sports broadcasting. Public trust is regarded as one of the most significant qualifications for sport commentators and this study used a Fuzzy AHP method in deciding the relative importance of professionalism, reliability, dynamic, and narrative skill. Based on the results, we conducted an evaluation of the public trust for the four SBS sport commentators for the 2010 South-Africa World Cup. The conclusion showed that professionalism and narrative skill were regarded as the most important factors for sport commentators to gain public trust. Among the four commentators evaluated, commentator # 1 got highest score overall, the soccer expert group highly appreciated commentator # 2, and the non-expert group highly appreciated commentator # 3.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.323-328
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• 2009

In this paper, a decentralized fuzzy output feedback controller for the nonlinear networked control system is proposed for wireless sensor network. Especially, it is assumed that the networked control system has the output packet loss and the input transmission failure. For the fuzzy control of the nonlinear subsystem, it presents Takagi-Sugeno (T-S) fuzzy model of each subsystem and it designs the decentralized fuzzy output feedback controller. The stability condition of the closed-loop system with the proposed controller is obtained by Lyapunov functional. The obtained stability condition is represented to the linear matrix inequality (LMI) form, and the control gain is obtained by LMI. An example is given to show the verification discussed throughout the paper.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.121-123
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• 1995

This paper presents a new method which compensates loss of loudness for digital hearing aids. Loudness grows more rapidly in frequency domain with substantial shifts of hearing threshold, so that loud sounds reach the uncomfortable sound level (UCL) at about the same physical stimulus level as with normal hearing. The result is a compression of the available dynamic range of hearing. Many techniques have been developed to compensate for hearing losses. In this paper, we propose a digital hearing aid which uses a single digital filter for reducing distortion and the fuzzy function to calculate gain factors. This function describes how much gain is needed for every frequency to restore loudness perception of a normal ear.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.78-86
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• 2003

Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.100-107
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• 2002

The advanced bilateral control algorithm, which can enlarge a reflected force by combining force reflection and compliance control, greatly enhances workability in teleoperation. In this scheme the maximum boundaries of a compliance controller and a force reflection gain guaranteeing stability and good task performance greatly depend upon characteristics of a slave arm, a master arm, and an environment. These characteristics, however, are generally unknown in teleoperation. It is, therefore, very difficult to determine such maximum boundary of the gain. The paper presented a novel method for design of an advanced bilateral controller. The factors affecting task performance and stability in the advanced bilateral controller were analyzed and a design guideline was presented. The neurofuzzy compliance model (NFCM)-based bilateral control proposed herein is an algorithm designed to automatically determine the suitable compliance for a given task or environment. The NFCM, composed of a fuzzy logic controller (FLC) and a rule-learning mechanism, is used as a compliance controller. The FLC generates compliant motions according to contact forces. The rule-learning mechanism, which is based upon the reinforcement learning algorithm, trains the rule-base of the FLC until the given task is done successfully. Since the scheme allows the use of large force reflection gain, it can assure good task performance. Moreover, the scheme does not require any priori knowledge on a slave arm dynamics, a slave arm controller and an environment, and thus, it can be easily applied to the control of any telerobot systems. Through a series of experiments effectiveness of the proposed algorithm has been verified.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.747-752
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• 2006

In this paper, the adaptive fuzzy sliding mode controller with two systems is designed. The existing sliding mode controller used to $approximation{\^{u}}(t)$ with discrete sgn function and sat function for keeping the state trajectories on the sliding surface[1]. The proposed controller decrease the disturbance for uncertain control gain and This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems ate used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system, we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem, and convergence and robustness properties ate demonstrated. Futhermore, fuzzy tuning improve tracking abilities by changing some sliding conditions. In the traditional sliding mode control, ${\eta}$ is a positive constant. The increase of ${\eta}$ has led to a significant decrease in the rise time. However, this has resulted in higher overshoot. Therefore the proposed ${\eta}$ tuning AFSMC improve the performances, so that the controller can track the trajectories faster and more exactly than ordinary controller. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.4
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• pp.324-328
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• 2012

With the recent advances in information retrieval, cross-media retrieval has been attracting lot of attention, but several issues remain problems such as constructing effective correlations, calculating similarity between different kinds of media objects. To gain better cross-media retrieval performance, it is crucial to mine the semantic correlations among the heterogeneous multimedia data. This paper introduces a new method for cross-media retrieval which uses ontology to organize different media objects. The experiment results show that the proposed method is effective in cross-media retrieval.