• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.7
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• pp.9-15
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• 2012

This paper is proposed the adaptive fuzzy neuro controller(AFNC) for high performance of induction motor drive. The design of this algorithm based on the AFNC that is implemented using fuzzy controller(FC) and neural network(NN). This controller uses fuzzy rule as training patterns of a NN. Also, this controller adjusts the weights between the neurons of NN to minimize the error between the command output and the actual output using the back-propagation method. The control performance of the AFNC is evaluated by analysis in various operating conditions. The results of analysis prove that the proposed control system has high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Composites Research
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• v.17 no.5
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• pp.7-14
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• 2004

This paper deals with adaptive fuzzy logic controller design to achieve proper dynamic response of a composite thin-walled beam with a tip mass. In order to check the effectiveness of this controller, three different types of control logic are selected and applied. The adaptive control capabilities provided by a system of piezoactuators bonded or embedded into the structure are also implemented in the system. Results show that the fuzzy logic controller is more effective than the proportional or velocity feedback controller for the vibration control of composite thin-walled beam with a tip mass.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.950-957
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• 2003

This paper deals with adaptive fuzzy logic controller design to achieve proper dynamic response of a composite thin-walled beam with a tip mass. In order to check the effectiveness of this controller, three different types of control logic are selected and applied. The adaptive control capabilities provided by a system of piezoactuators bonded or embedded into the structure are also implemented in the system. Results show that the fuzzy logic controller is more effective than the proportional or velocity feedback controller for the vibration control of composit thin-walled beam with a tip mass.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.419-422
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• 1998

This paper presents how to design speed control of wound rotor induction motors with slip energy recovery. The speed is limited at some range of sub-synchronous speed of the rotating magnetic field. The problem with speed control by adjusting resistance value in the rotor circuit reduces the efficiency of power, because of the slip energy is lost when it passes through the rotor resistance. The control system is designed to maintain efficiency of motor, where it recovers loss energy by returning it to the system to improve the efficiency. A new PI control method of adaptive control [1］,［13］is applied for the system with cascade type PI controller on the main loop to keep the speed constant and the internal loop to adjust the rotor appropriated current of the load provides the good transient response without overshoot.

• The Transactions of the Korean Institute of Power Electronics
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• v.2 no.1
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• pp.39-45
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• 1997

In this paper, a high speed motor drive system using an indirect adaptive neural network controller is proposed. In the variable high speed motor drives, the speed response can be deteriorated by long settling time and high overshoot. To obtain a good dynamical performance, an adaptive feedforward controller consisted of Neural Network Controller(NNC) and Neural Network Emulator(NNE) is applied. The NNE is used to identify the parameters and characteristics of high speed motor. To train the controller, the weights are dynamically adjusted using the back propagation algorithm. Computer simulation and implementation of the proposed system is described.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.2
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• pp.144-150
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• 2002

In this paper a design of neuro-fuzzy-based predictive controller for nonlinear systems with time-delay is proposed. The proposed control system contains two neuro-fuzzy systems called ANFIS(Adaptive Neuro-Fuzzy Inference System). One is run as a series-parallel mode and the other is run as a parallel mode. An ANFIS running in series-parallel mode emulates the response of the nonlinear system with time-delay. Another ANFIS running in parallel mode generates the predicted output of the nonlinear system to compensate for the time-delays. Therefore, the proposed control system can be thought of as an extension of Smith-predictor scheme to the nonlinear systems with time-delay. A detailed design Procedure is presented and finally computer simulations are executed for the effectiveness of the proposed control scheme.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.6
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• pp.537-543
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• 2016

A new approach to systematically model aerodynamic coefficients using an adaptive sampling based wind tunnel testing considering cost is proposed. The Latin Hypercube design is used for selecting initial test points. The Gaussian Process (GP) is iteratively used during the experiment to determine additional experimental points that minimizes the uncertainty reduction per incremental cost. A numerical simulation based experiment was conducted using the static aerodynamic coefficient database a fighter aircraft, which demonstrated the validity of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.154-157
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• 2006

This paper is proposed hybrid artificial intelligent(HAI) controller for high performance of induction motor drive. The design..of this algorithm based on fuzzy-neural network(FNN) controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Smart Structures and Systems
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• v.11 no.3
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• pp.315-329
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• 2013

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

• Proceedings of the KIEE Conference
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• 2003.07e
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• pp.62-69
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• 2003

In recent years, data transmission using power lines has been much highlighted. Power line is known to be cost-effective communication medium because the entire cable infrastructure has been already established and it is entirely connected with any home. Recently, the target of researches is to communicate data reliably over power lines at the speed of at least 1Mbits/s over the frequency range from 1MHz to 10MHz. OFDM communication system has been used for the high speed data transmission. Next, the conventional and adaptive OFDM systems for high speed data transmission over power line channel are investigated. The performance of AOFDM(adaptive OFDM) over the frequency selective channel with impulsive and narrow-band noise are studied to be a nice solution for high speed data transmission over power lines. The simulation results show that data the rates of the AOFDM are improved about 47% more than the ones of the conventional OFDM over the frequency response of case 4. In the results, the data rate has been much improved by the proposed adaptive algorithm in the frequency selective channel.