• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1593-1598
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• 2012

In this paper, we propose an intelligent signal control method based on fuzzy logic applicable in real time. We design membership functions to model occupied time and the number of vehicles for each lane. A priority for each signal phase is computed by the popular Max-Min fuzzy inference based on control rules and membership degrees of prepared two functions at any given time. A tie breaking scheme is considering weighted sum of the rate of occupied time per number of vehicles in that block and the standard deviation of these blocks. Only a signal phase with the highest priority is opened and all others are closed and the duration of the phase opening is computed proportional to the rate of number of weighting vehicles in that signal per all weighted vehicles. The simulation result shows that the proposed method is more efficient than the static control in all simulation conditions in $2{\times}3$ experimental designs with the number of vehicles in intersection and congestion degrees that have all three levels.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.180-189
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• 2009

Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver's intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.318-322
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• 2016

A quad-copter or quad rotor system is an unmanned flying machine having four engines, which their thrust force is produced by four propellers. Its stable control is very important and has widely been studied. It is a typical example of a nonlinear system. So, it is difficult to get a desired control performance by conventional control algorithms. In this paper, we propose the design of a vectored sum defuzzification based fuzzy logic system for the hovering control of a quad-copter. We first summarize its dynamics and introduce a vectored sum defuzzification scheme. And then we design a vectored sum defuzzification based fuzzy logic system. for the hovering control of the quad-copter. Finally, in order to check the feasibility of the proposed system we present some simulation examples.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.140-146
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• 2016

This paper proposes a control method of the Segway with unknown control coefficient and input saturation. To design a simple controller for the Segway with the model uncertainty, the prescribed performance function is used. Furthermore, an auxiliary variable is introduced to deal with unknown time-varying control coefficient and input saturation problem. Due to the auxiliary variable, function approximators are not used in this paper although all model uncertainties are unknown. Thus, the controller can be simple. From the Lyapunov stability theory, it is proved that all errors of the proposed control system remain within the prescribed performance bounds. Finally, the simulation results are presented to demonstrate the performance of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.109.1-109
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• 2001

This paper deals with the path following problem of car-like intelligent mobile robot. A robust sliding mode control law based on time-varying state feedback is performed via Lyapunov method for path tracking of nonholonomic mobile robot with uncertainties. At first, A sliding control law is designed by combing the natural algebraic structure of the chained form system with ideas from sliding mode theory. Then, a robust control law is proposed to impose robustness against bounded uncertainties in path tracking. The problem of estimating the asymptotic stability region and the sliding domain of uncertain sliding mode system with bounded control input is also discussed. The proposed sliding mode control law can ensure the global reaching condition of the uncertain control system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.3
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• pp.154-163
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• 2013

In this paper, we propose a formation control algorithm for underactuated autonomous underwater vehicles (AUVs) with parametric uncertainties using the approach angle. The approach angle is used to solve the underactuated problem for AUVs, and the leader-follower strategy is used for the formation control. The proposed controller considers the nonzero off-diagonal terms of the mass matrix of the AUV model and the associated parametric uncertainties. Using the state transformation, the mass matrix, which has nonzero off-diagonal terms, is transformed into a diagonal matrix to simplify designing the control. To deal with the parametric uncertainties of the AUV model, a self-recurrent wavelet neural network is used. The proposed formation controller is designed based on the dynamic surface control technique. Some simulation results are presented to demonstrate the performance of the proposed control method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.35-38
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• 1998

Abstracts In this paper, we propose a robust adaptive fuzzy control scheme using a sliding control input for tracking of a class of MISO nonlinear systems with unknown bounded external disturbances. In the proposed scheme, the nonlinearity is estimated adaptively via a fuzzy inference based on a fuzzy model. A sliding control input is introduced such that boundedness of all signals in the system is guaranteed even though the existence of a fuzzy approximation error and external disturbances. The controller parameters are updated by using a proposed adaptation law, which is similar 1-modification method. Computer simulation shows the effectiveness of the proposed control scheme.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.77-83
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• 2011

In this paper, an active backstepping design is proposed to achieve control and synchronization of a new hyperchaotic system. The proposed method is a systematic design approach and exists in a recursive procedure that interlaces the choice of a Lyapunov function with the design of the active control. The proposed controller enables stabilization of chaotic motion to the origin as well as synchronization of the two identical new hyperchaotic systems. Numerical simulations illustrate the validity of the proposed control technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.945-961
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• 2019

Tongue diagnosis is one of the most important diagnostic methods in Traditional Chinese Medicine (TCM). Tongue image segmentation aims to extract the image object (i.e., tongue body), which plays a key role in the process of manufacturing an automated tongue diagnosis system. It is still challenging, because there exists the personal diversity in tongue appearances such as size, shape, and color. This paper proposes an innovative segmentation method that uses image thresholding, gray projection and active contour model (ACM). Specifically, an initial object region is first extracted by performing image thresholding in HSI (i.e., Hue Saturation Intensity) color space, and subsequent morphological operations. Then, a gray projection technique is used to determine the upper bound of the tongue body root for refining the initial object region. Finally, the contour of the refined object region is smoothed by ACM. Experimental results on a dataset composed of 100 color tongue images showed that the proposed method obtained more accurate segmentation results than other available state-of-the-art methods.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.287-293
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• 2007

This paper proposed modelling and design method in suspension system design to analyze active suspension equipment by adopting intelligent robust control theory. Recent in the field of suspension system design it is general to adopt active control scheme for stiffness and damping, and connection with other vehicle stability control equipment is also intricate, it is required for control system scheme to design more robust, higher response and precision control equipment. It is known that active suspension system is better than passive spring-damper system in designing suspension equipment. We analyze suspension system with considering location of front-rear wheel and driving velocity, then design robust control system. Numerical example is shown for validity of intelligent control system design in active suspension system.