• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.268-271
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• 2001

This paper describes the power factor control of doubly fed induction machine using fuzzy logic algorithm in wind power generation system. Under fuzzy logic control, which enables superior dynamic performance, the power factor is independently controllable by decoupled d, q rotor experimental results are presented.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.249-254
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• 2001

Abstract In this paper, we propose a method of cooperative control based on artifical intelligent system in distributed autonomous robotic system. In general, multi-agent behavior algorithm is simple and effective for small number of robots. And multi-robot behavior control is a simple reactive navigation strategy by combining repulsion from obstacles with attraction to a goal. However when the number of robot goes on increasing, this becomes difficult to be realized because multi-robot behavior algorithm provide on multiple constraints and goals in mobile robot navigation problems. As the solution of above problem, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for obstacle avoidance. Here, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for their direction to avoid obstacle. Our focus is on system of cooperative autonomous robots in environment with obstacle. For simulation, we divide experiment into two method. One method is motor schema-based formation control in previous and the other method is proposed by this paper. Simulation results are given in an obstacle environment and in an dynamic environment.

• Transactions of The Korea Fluid Power Systems Society
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• v.2 no.4
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• pp.1-6
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• 2005

This paper presents optimization of a pneumatic control system whose design parameters have been optimized so that the desired dynamic characteristics of cylinder position was obtained. The pneumatic system is used as transferring and stacking equipment for solid freeform fabrication system which has been widely used in design verification applications. The pneumatic system mainly consists of pneumatic control valves and cylinders. The system was modeled by using several principles for pneumatic components. The system was optimized to obtain dynamic performance with enough damping to reduce cylinder vibration. A fuzzy controller has been applied to fulfill the dynamic performance requirements of the pneumatic system. The simulation results show that the fuzzy controller is more effective than a PD controller.

• 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

• 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.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.138-138
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• 2000

In this paper, a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a prefilter, the inverse dynamic model of a system and a fuzzy logic controller. The prefilter prevents high frequency effects from the inverse dynamic model. The model of the system is characterized by a nonlinear equation with coulomb friction. The fuzzy logic controller regulates the error between the set-point and the system output which may be caused by disturbances and it simultaneously traces the change o( the reference input. The parameters of the model are estimated by a genetic a]gorithm. An experimental work on a DC motor system is carried out to illustrate the performance of the proposed controller

• Journal of Mechanical Science and Technology
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• v.18 no.4
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• pp.535-549
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• 2004

This paper proposes a sliding mode controller with fuzzy adaptive perturbation compensator(FAPC) to get a good control performance and reduce the chatter, The proposed algorithm can reduce the chattering because the proposed fuzzy adaptive perturbation compensator compensates the perturbation terms. The compensator computes the control input for compensating unmodeled dynamic terms and disturbance by using the observer-based fuzzy adaptive network(FAN) The weighting parameters of the compensate. are updated by on-line adaptive scheme in order to minimize the estimation error and the estimation velocity error of each actuator. Therefore, the combination of sliding mode control and fuzzy adaptive network gives the robust and intelligent routine to get a good control performance. To evaluate the control performance of the proposed approach, tracking control is experimentally carried out for the hydraulic motion platform which consists of a 6-DOF parallel manipulator.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.3
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• pp.34-40
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• 2001

Robot manipulator has highly nonlinear dynamics. Therefore the control of multi-link robot arms is a challenging and difficult problem. In this paper a decentralized adaptive fuzzy sliding mode scheme is developed for control of robot manipulators. The proposed scheme does not require an accurate manipulator dynamic model, yet it guarantees asymptotic trajectory tracking despite gross robot parameter variations. Numerical simulation for decentralized control of a 3-axis PUMA arm will also be included.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.425-429
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• 1996

Our unicycle has simple mechanical structure. But unicycle's dynamic system is a very sensitive unstable nonlinear system. In this paper, a fuzzy inference control mechanism was established throughout an inquiry into human riding a unicycle, and we developed a direct fuzzy controller to control our unicycle robot. This proposed fuzzy controller is consisted with fuzzy logic controllers for attitude stability and wheel's velocity. Computer simulation results show that our fuzzy controller has very powerful performance to unstable nonlinear unicycle robot system.