• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.8
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• pp.11-18
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• 1995

This paper proposes a nonlinear adaptive equalizer which is based on fuzzy rules and fuzzy inference of several affine mapping for the received channel data. The proposed nolonlinear adaptive equalizers with the significantly lower computational complexity. Also it can be applied to the on-line adaptation environments owing to its fast convergence characteristics and the lower computational load. When using the decision feedback vectors, this equaalizer can be easily realized in the form of the DFE structure with out the requirement for the perfect channel knowledge as in the case of the fuzzy adaptive filter.

• Kyungpook Mathematical Journal
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• v.52 no.2
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• pp.189-200
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• 2012

In this article we introduce the class of I-convergent double sequences of fuzzy real numbers. We have studied different properties like solidness, symmetricity, monotone, sequence algebra etc. We prove that the class of I-convergent double sequences of fuzzy real numbers is a complete metric spaces.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.11
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• pp.3560-3572
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• 1996

This paper presents a new discrete-time fuzzy-sliding mode controller for robust vibration control of a smart structure featuring a piezofilm actuator. A governong equation of motion for the smart beam structure is derived and discrete-time codel with mismatched uncertainties such as parameter variations is constructed ina state space. A discrete-time sliding mode control system consisting of an equivalent controller and a discontinuous controller is formulated. In the design of the equivalent part, so called an equivalent controller separation method is adopted to achieve vzster convergence to a sliding surface without extension of a sliding region, in which the system robustness maynot be guaranteed. On the other hand, the discontinuous part is constructed on the basis of both the sliding and the convergence conditions using a time-varying feedback gain. The sliding moide controller is then incorporated with a fuzzy technique to appropriately determine principal control parameters such as a discountinuous feedback gain. Experimental implementation on the forced and random vibraiton controls is undertaken in order to demonstrate superior control performance of the proposed controller.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.4
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• pp.403-411
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• 2001

A criterion for evaluation of burners has changed recently, and the environmental problems are raised as a global issue. Burners with higher thermal efficiency and lower oxygen in the exhaust gas, evaluated better. To comply with environmental regulations, burners must satisfy the $NO_x$ and CO regulation. Consequently. 'good burner' means one whose thermal efficiency is high under the constraint of $NO_x$ and CO consistency. To make existing burner satisfy recent criterion, it is highly recommended to develop a feedback control scheme whose output is the consistency of $NO_x$ and CO. This paper describes the development of a real time flame diagnosis technique that evaluate and diagnose the combustion states, such as consistency of components in exhaust gas, stability of flame in the quantitative sense. In this paper, it was proposed on the flame diagnosis technique of burner using Neuro- Fuzzy algorithm. This study focuses on the relation of the color of the flame and the state of combustion. Neuro- Fuzzy learning algorithm is used in obtaining the fuzzy membership function and rules. Using the constructed inference algorithm, the amount of $NO_x$ and CO of the combustion gas was successfully inferred.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.3
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• pp.157-162
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• 2005

This paper presents an adaptive compensator using the fuzzy systems for robot manipulator with unknown frictions. In general, frictions are neglected or dynamic frictions are only considered in robot control theories. The proposed control method considers viscous frictions as well as dynamic frictions. Using the property that the frictions of joints are decoupled, SISO-fuzzy systems are utilized to approximate each friction. The stability of overall control system is proven and the adaptive laws are derived based on Lyapunov stability theorey. To verify the validity of the proposed control strategy, the results of computer simulations are shown for 2-link robot manipulator. The ability of approximating of the fuzzy system is also shown.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1271-1279
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• 2017

A highly accurate model-free controller is proposed for trajectory tracking control of robot manipulators. The proposed controller incorporates time-delay estimation (TDE) to estimate and cancel continuous nonlinearities of robot dynamics, and exploits fuzzy logic systems to suppress the effect of the TDE error, which is due to discontinuous nonlinearities such as friction. To this end, integral sliding mode is defined using desired error dynamics, and a Mamdani-type fuzzy inference system is constructed. As a result, the proposed controller achieves the desired error dynamics well. Implementation of the proposed controller is easy because the design of the controller is intuitive and straightforward, and calculations of the complex robot dynamics are not required. The tracking performance of the proposed controller is verified experimentally using a 3-degree of freedom PUMA-type robot manipulator.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.54-60
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• 2002

In this paper, we proposed a hybrid neural network-fuzzy controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of loaming a inverse model neural network of Plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed speed controller get a good response compare with a neural network controller. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.1
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• pp.17-32
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• 1992

The multi-layer neural network that has broadly been utilized in designing the controller of robot manipulator possesses the desirable characteristics of learning capacity, by which the uncertain variation of the dynamic parameters of robot can be handled adaptively, and parallel distributed processing that makes it possible to control on real-time. However the error back propagation algorithm that has been utilized popularly in the learning of the multi-layer neural network has the problem of its slow convergence speed. In this paper, an approach to improve the convergence speed is proposed using the fuzzy logic that can effectively handle the uncertain and fuzzy informations by linguistic level. The effectiveness of the proposed algorithm is demonstrated by computer simulation of PUMA 560 robot manupulator.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.427-433
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• 2019

This paper propose a fuzzy inference model for map building and navigation for a mobile robot with an active camera, which is intelligently navigating to the goal location in unknown environments using sensor fusion, based on situational command using an active camera sensor. Active cameras provide a mobile robot with the capability to estimate and track feature images over a hallway field of view. In this paper, instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. Command fusion method is used to govern the robot navigation. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of active camera sensor for navigation experiments are fused into the identification process. Navigation performance improves on that achieved using fuzzy inference alone and shows significant advantages over command fusion techniques. Experimental evidences are provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the active camera and the feature images.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.323-326
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• 2002

In this paper, we consider Choquet integrals of interval number-valued functions(simply, interval number-valued Choquet integrals). Then, we prove convergence theorem for interval number-valued Choquet integrals with respect to an autocontinuous fuzzy measure.