• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.182-182
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• 2000

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that the selected solution become the global optimal solution by optimizing the Akaike's information criterion. The trajectory trucking experiment of the polishing robot system shows that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding model controller provides reliable tracking performance during the polishing process.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.110-110
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• 2000

In this paper, an antilock brake system (ABS) for commercial vehicles is studied by considering the design of a fuzzy Logic controller with pulse width modulation (PWM). PWM method is used for generating solenoid valve inputs in order to cope with the chattering problem caused by the conventional on/off control The sliding mode observer is designed to estimate the vehicle longitudinal velocity and it is used to calculate the wheel slip ratio. The effectiveness of the proposed control algorithm was validated by simulations performed with a nonlinear 14-DOF vehicle model including the dynamics of the brakes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.32-33
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• 2014

This paper presents control performances of a seat suspension system equipped with magnetorheological (MR) dampers using a new adaptive fuzzy sliding mode controller (FSMC). Adaptive fuzzy controller is formulated by considering the acceleration of the seat. It has been demonstrated that the proposed seat suspension system realized by the adaptive fuzzy sliding mode controller can provide effective performances such as reduced vibration.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.7
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• pp.29-40
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• 2009

This paper proposes a modeling and controller design approach for a hybrid wind power generation system that considers a fixed wind-turbine and a dump load. Since operating conditions are kept changing, it is challenge to design a control for reliable operation of the overall system To consider variable operating conditions, Takagi-Sugeno (TS) fuzzy model is taken into account to represent time-varying system by expressing the local dynamics of a nonlinear system through sub-systems, partitioned by linguistic rules. Also, each fuzzy model has uncertainty. Thus, in this paper, a modem nonlinear control design technique, the sliding mode nonlinear control design, is utilized for robust control mechanism In the simulation study, the proposed controller is compared with a proportional-integral (PI) controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-hybrid power generation system.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.973-979
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• 2001

Sliding mode control guarantees robustness in the presence of modeling uncertainties and external disturbances. However, this can be obtained at the cost of high control activity that may lead to chattering As one way to alleviate this problem a boundary layer around sliding surface is typically used. In this case the selection of controller gain, control ban width and boundary layer thickness is a crucial problem for the trade-off between tracking error and chattering. The parameter tuning is usually done by trail-and-error in practice causing significant effort and time. An auto tuning method based on fuzzy rules is proposed in the paper in this method tracking error and chattering are monitored by performance indices and the controller tunes the design parameters intelligently in order to compromise both indices. To demonstrate the efficiency of the propose method a mass-spring translation system and a roboic control system are simulated and tested It is shown that the proposed algorithm is effective to facilitae the parameter tuning for sliding mode controllers.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.449-452
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• 1997

In this paper, we suggest a variable structure controller using the time-varying nonlinear sliding surface instead of the fixed sliding surface, which has been the robustness against parameter variations and extraneous disturbance during the reaching phase. As appling TS fuzzy algorithm to the regulation of the nonlinear sliding surface, the reaching time of the system trajectory is faster than the fixed method . This proposed scheme has better performance than the conventional method in reaching time parameter variation and extraneous disturbance. To demonstrate its performance, the proposed control algorithm is applied to a rotational inverted pendulum.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.226-228
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• 2006

This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems are 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 are demonstrated. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.361-365
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• 1998

In this paper, the sliding mode variable structure-fuzzy(SMVS-F) control algorithm is applied to speed controller for field oriented induction motor drive system. According to the principle of sliding mode variable structure-fuzzy adjustable speed control scheme, the proposed algorithm shows good performances which are reducing chattering, robustness against parameter variation in induction motor drive. The validity of the proposed control scheme is verified by computer simulation using SIMULINK.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.210-214
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• 1998

Radio-Controlled helicopter has superior movement abilities like as hovering or backward move. So it has been used as a sprinkler of agricultural medicines or an observer of dangerous area such as a volcano, etc. But its operation is not simple because it has many control factors and they interfere with each other. Therefore the helicopter is not controlled by simple theory in the case of automatic operation. Then fuzzy sliding mode control, which has fastness, fineness and robustness, is thought to be suitable to satisfy various requirements of the helicopter operation. In this work, the fuzzy sliding mode control was applied to the flying of RC helicopter, As tile result, it was controlled with good performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.752-758
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• 2004

In this paper, we proposed an adaptivefuzzy sliding control algorithm using gradient descent method to reduce chattering phenomenon which is viewed in variable control system. In design of FLC, fuzzy control rules are obtained from expert's experience and intuition and it is very difficult to obtain them. We proposed an adaptive algorithm which is updated by consequence part parameter of control rules in order to reduce chattering phenomenon and simultaneously to satistfy the sliding mode condition. The proposed algorithm has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties in the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.