• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2005.03a
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• pp.513-520
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• 2005

An active modal-fuzzy control method using hydraulic actuators is presented for seismic response reduction. In the proposed control system, a new fuzzy controller designed in the modal space produces the desired active control force. This type controller has all advantages of the fuzzy control algorithm and modal approach. Since it is very difficult to select input variables used in fuzzy controller among an amount of state variables in the active fuzzy control system, the presented algorithm adopts the modal control algorithm which is able to consider more easily information of all state variables in civil structures that are usually dominated by first few modes. In other words, all information of the whole structure can be considered in the control algorithm evaluated to reduce seismic responses and it can be efficient for especially civil structures. In addition, the presented algorithm is expected to magnify utility and performance caused by efficiency that the fuzzy algorithm can handle complex model more easily. An active modal-fuzzy control scheme is applied together with a Kalman filter and a low-pass filter to be applicable to real civil structures. A Kalman filter is considered to estimate modal states and a low-pass filter was used to eliminate spillover problem. The results of the numerical simulations for a wide amplitude range of loading conditions show that the proposed active modal-fuzzy control system can be beneficial in reducing seismic responses of civil structures.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2270-2273
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• 2003

Fuzzy logic control has been widely implemented in air conditioning and ventilation systems which has uncertainty or high robust system. Since the dynamic behaviors of the systems contain complexity and uncertainty in its parameters , several fuzzy logic controllers had been implemented to control room temperature in the field of air conditioning system. In this paper, the fuzzy logic control has been developed to control room temperature and humidity in the precision air conditioning systems. The nonlinear mathematical model was formulated using energy and continuity equations. MATLAB was used to simulate the fuzzy logic control of the multi-variable air conditioning systems. The simulation results show that fuzzy logic controller can reduce the steady-state errors of the room temperature and relative humidity in multivariable air conditioning systems. The offset are less than 0.5 degree Celsius and 3 percent in relative humidity respectively under random step disturbance in heating load and moisture load respectively

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1474-1477
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• 2005

This paper is proposed maximum torque per ampere of induction motor using fuzzy-neural networks controller. Operation of maximum torque per ampere is achieved when, at a given torque and speed, the slip frequency is adjusted to that so that the stator current amplitude is minimized. This paper introduces a induction motor drive system with fuzzy-neural networks controller. A neural network-based architecture is described for fuzzy logic control. The characteristic rule and their membership function of fuzzy system are represented as the processing nodes in the neural network structure. This paper is proposed the analysis as well as the simulation results to verify the effectiveness of the new method.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1127-1128
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• 2008

In this paper, we propose a control method to improve control performance for a Quad-rotor Unmanned Aerial Vehicle's stabilization. The proposed method is the Fuzzy+I control that contains a fuzzy controller which processes signals from the error and the change of error, and generates the control signal by summing up fuzzy output signal and integral signal. We simulated and experimented on the fuzzy+I control method by implementing Quad-rotor UAV that is able to hovering, for the purpose of verifying the effectiveness of the proposed fuzzy+I control method in comparison with general PID control, and we found out that fuzzy+I controller improved control performance of the system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.7 s.94
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• pp.1813-1822
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• 1993

An algorithm of fuzzy variable structrue control is proposed to design a closed loop fuel-injection system for the emission control of automotive gasoline engines. Fuzzy control is combined with sliding control at the switching boundary layer to improve the chattering of the stoichiometric air to fuel ratio. Multi-staged fuzzy rules are introduced to improve the adaptiveness of control system for the various operating conditions of engines, and a simplified technique of fuzzy inference is also adopted to improve the computational efficiency based on nonfuzzy micro-processors. The proposed method provides an effective way of engine controller design due to its hybrid structure satisfying the requirements of robustness and stability. The great potential of the fuzzy variable structure control is shown through a hardware-testing with an Intel 80C186 processor for controller and a typical engine-only model on an AD-100 computer.

• Smart Structures and Systems
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• v.19 no.5
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• pp.577-585
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• 2017

In this paper, an adaptive fuzzy sliding mode controller (AFSMC) is designed to reduce dynamic responses of seismically excited structures. In the conventional sliding mode control (SMC), direct implementation of switching-type control law leads to chattering phenomenon which may excite unmodeled high frequency dynamics and may cause vibration in control force. Attenuation of chattering and its harmful effects are done by using fuzzy controller to approximate discontinuous part of the sliding mode control law. In order to prevent time-consuming obtaining of membership functions and reduce complexity of the fuzzy rule bases, adaptive law based on Lyapunov function is designed. To demonstrate the performance of AFSMC method and to compare with that of SMC and fuzzy control, a linear three-story scaled building is investigated for numerical simulation based on the proposed method. The results indicate satisfactory performance of the proposed method superior to those of SMC and fuzzy control.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.276-281
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• 2010

The switched reluctance motor (SRM) is an older member of the electric machines family. Its simple structure, ruggedness and inexpensive manufacturing potential make it extremely attractive for industrial applications. However, these merits are overshadowed by its inherent high torque ripple, acoustic noise and difficulty to control. In this paper, a control strategy of the angle position control for the SRM drive based on fuzzy logic is illustrated. The input control parameter, the output control parameter and fuzzy control with FAM table formulation strategy are described and simulated with control patterns, and the decision form of the fuzzy control is illustrated and simulated, and the scope of implementing in a Fuzzy based ASIC chip is enlightened with literature support.

• International Journal of Air-Conditioning and Refrigeration
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• v.15 no.2
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• pp.61-69
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• 2007

This paper deals with fuzzy control with a feedforward compensator to progress both energy saving and coefficient of performance (COP) in a variable speed refrigeration system. Both the capacity and superheat are controlled simultaneously and independently in the system. By adopting the fuzzy theory, the controller design for the capacity and superheat is possible without depending on a dynamic model of the system. Moreover, the feedforward compensator of the superheat can reduce influence of the interfering loop between the capacity and superheat. Some experiments are conducted to design appropriate fuzzy controller by an iteration manner. The results show that the proposed fuzzy controller with the compensator can establish good control performances for the complicated refrigeration system in spite of its inherent strong non-linearity. Also, the fuzzy control performances were investigated by comparing to the model based PI control experimental results to evaluate transient behavior under the control.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.443-446
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• 2004

This paper discusses an intelligent digital redesign technique for designing a fuzzy pulse-width-modulated (PWM) control. First when we are given a well-designed fuzzy analog control, the equivalent digital control is intelligently redesigned. Using the similar technique we intelligently redesign the fuzzy PWM control from the intelligently redesigned fuzzy digital control. A stabilizability of the intelligently redesigned PWM control is rigorously analyzed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.200-208
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• 2014

This paper presents the control of an inverted pendulum system using intelligent algorithms, such as fuzzy logic and neural networks, for advanced control education. The swing up balancing control of the inverted pendulum system was performed using fuzzy logic. Because the switching time from swing to standing motion is important for successful balancing, the fuzzy control method was employed to regulate the energy associated with the angular velocity required for the pendulum to be in an upright position. When the inverted pendulum arrived within a range of angles found experimentally, the control was switched from fuzzy to proportional-integral-derivative control to balance the inverted pendulum. When the pendulum was balancing, a joystick was used to command the desired position for the pendulum to follow. Experimental results demonstrated the performance of the two intelligent control methods.