• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.690-696
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• 2004

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• Journal of KSNVE
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• v.9 no.1
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• pp.33-41
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• 1999

This paper presents a method of actively controlling the interior noise by a trim panel with hybrid feedforward-feedback control loop. The control technique is designed to minimize the vibration of panel whose motion is limited to that of a piston (out-of-plane motion). The hybrid controller consists of an adaptive feedforward controller in conjunction with a linear quadratic Gaussian (LQG) feedback controller. In order to maintain control performance of both persistent and transient disturbances, the feedback loop speeds up the adaptation rate of feedforward controller by improving damping capacity of secondary plant related with the adaptation rule. Numerical simulation and experimental result indicate that the hybrid controller is a more effective method for reducing the vibration of the panel (and therefore the interior noise) compared to using feedforward controller.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.2
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• pp.239-245
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• 2015

In order to control the hybrid power system efficiently, the knowledge for the required load of the system is important. The agricultural tractor performs various farm works such as plow, rotary, and baler. When it performs rotary tillage and baler operation, the generated work load is analyzed. To analyze trend of work load, moving average technique is applied to the measurement data. Optimal control inputs for the two works are obtained from simulation using the dynamic programming. The novel fundamental control strategy for parallel hybrid tractor called Max. SOC is proposed.

• Journal of Power Electronics
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• v.11 no.4
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• pp.393-400
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• 2011

The main objective of this paper is to control the speed of Nonlinear Hybrid Electric Vehicle (HEV) by controlling the throttle position. Various control techniques such as well known Proportional-Integral-Derivative (PID) controller in conjunction with state feedback controller (SFC) such as Pole Placement Technique (PPT), Observer Based Controller (OBC) and Linear Quadratic Regulator (LQR) Controller are designed. Some Intelligent control techniques e.g. fuzzy logic PD, Fuzzy logic PI along with Adaptive Controller such as Self Organizing Controller (SOC) is also designed. The design objective in this research paper is to provide smooth throttle movement, zero steady-state speed error, and to maintain a Selected Vehicle (SV) speed. A comparative study is carried out in order to identify the superiority of optimal control technique so as to get improved fuel economy, reduced pollution, improved driving safety and reduced manufacturing costs.

• Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.137-147
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• 2015

In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

• Journal of Power Electronics
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• v.7 no.3
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• pp.213-221
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• 2007

A digital state feedback control method for the current mode control of DC-DC converters is proposed in this paper. This approach can precisely achieve interleaved current sharing among the converter modules. As the controller design and system analysis are performed in the time domain, the proposed method can easily satisfy the required converter specification by using the pole placement technique. The digital state feedback controller in the continuous and discrete time domain is derived for the robust tracking control. For the verification of the proposed control scheme, a parallel module bi-directional converter in a prototype 42V/14V hybrid automotive power system, which is a design example in the continuous time domain, and a parallel module buck converter, which is a design example in the discrete time domain, are implemented using a TMS320F2812 digital signal processor (DSP).

• Journal of Agricultural Extension & Community Development
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• v.22 no.1
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• pp.43-54
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• 2015

This study explored the effects of adoption of innovation and resistant attitude on farmers' perspectives and also was deigned for developing prompt spread of ICT and facilitating stronghold support center in the convergence agricultural field. To closely examine the variation for exploitation intent of stronghold support center in the ICT convergence agriculture, 110 farmers who had experienced introduction for ICT hybrid environmental control system were participated in the study using the questionnaire. The results revealed the several findings. Firstly, there was no significant differences between the self-efficacy such as confidence of application technology for farmers and adoption of innovative technique (p=.075). Secondly, suitability of using ICT hybrid environmental control system showed a significant difference in the adoption of innovation (p=2.750) while complexity of using ICT hybrid environmental control system indicated the negative effects on the adoption of innovation (p=3.591). Thirdly, introduction cost of ICT hybrid environmental control system showed the negative effects in the adoption of innovation (p=2.278), whereas adoption of innovation indicated a significant difference in the stronghold support center in the convergence agricultural field (p=5.500). Finally, resistance of ICT adoption of innovative technique revealed the negative effects on the stronghold support center in the ICT convergence agriculture. This study, therefore, demonstrated that educational assistance for acquiring ICT technique, suggestion of influences for productivity, and development for skills were needed to extend ICT convergence technology. Additionally, the study indicated the strategies related with promotion as well as ways of minimizing introduction cost.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.72-81
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• 2000

In this paper, we design an adaptive neuro-fuzzy inference system(ANFIS) precompensator for load frequency control of 2-area power systems. While proportional integral derivative (PID) controllers are used in power systems, they may have some problems because of high nonlinearities of the power systems. So, a neuro-fuzzy-based precompensation scheme is incorporated with a convectional PID controller to obtain robustness to the nonlinearities. The proposed precompensation technique can be easily implemented by adding a precompensator to an existing PID controller. The applied neruo-fuzzy inference system precompensator uses a hybrid learning algorithm. This algorithm is to use both a gradient descent method to optimize the premise parameters and a least squares method to solve for the consequent parameters. Simulation results show that the proposed control technique is superior to a conventional Ziegler-Nichols PID controller in dynamic responses about load disturbances.

• Journal of Welding and Joining
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• v.25 no.6
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• pp.71-77
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• 2007

Until now, many researches on laser-arc hybrid welding processes have been conducted mainly for high power CW laser and high direct current arc to weld the thick steel plates for shipbuilding. Recently, however the usage of thin steel plates, which tend to be deformed easily by thermal energy, is been increasing because of demand of light structure such as car body in the automobile industry. Accordingly, heat sources having relatively low heat input such as pulsed laser, dip-transfer DC GMA and pulsed GMA seem to be applied more increasingly and the study about those heat sources is needed more intensively. Any heat source mentioned above can not stand alone without weld defects at a relatively high welding speed for increasing the welding productivity. This is main reason to apply the hybrid welding process which uses pulsed laser and low-heat-input GMA heat sources simultaneously to weld the thin steel plate. In this study, parameters of pulsed laser and dip-transfer DC GMA welding are studied firstly through preliminary experiments, and then analyzed in the viewpoint of their physical phenomena. Before conducting the hybrid welding, a pulse control technique is developed based on the parallel port communication and Visual C++ 6.0. Owing to development of this technique, interactions of laser and arc pulses can be controlled consistently. Using the pulse control technique, the hybrid welding is conducted and then its interactive welding phenomenon is analyzed.

• Structural Engineering and Mechanics
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• v.36 no.2
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• pp.181-195
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• 2010

Coupled building control is a viable method to protect tall buildings from seismic excitation. In this study, the semi-active control of a building complex is investigated for mitigating seismic responses. The building complex is formed of one main building and one podium structure connected through Magneto-Rheological (MR) Dampers and Tuned Mass Damper. The conventional semi-active control techniques require a primary controller as a reference to determine the desired control force, and modulate the input voltage of the MR damper by comparing the desired control force. The fuzzy logic directly determines the input voltage of an MR damper from the response of the MR damper. The control performance of the proposed fuzzy control technique for the MR damper is evaluated for the control problem of a seismically-excited building complex. In this paper, a building complex that include a 14-story main building and an 8-story podium structure is applied as a numerical example to demonstrate the effectiveness of semi-active control with Magneto-Rheological dampers and its comparison with the passive control with the Tuned Mass Damper and two uncoupled buildings and hybrid semi-active control including the Tuned Mass Damper and Magneto-Rheological dampers while they are subject to the earthquake excitation. The numerical results show that semi-active control and hybrid semi-active control can significantly mitigate the seismic responses of both buildings, such as displacement and shear force responses, and fuzzy control technique can effectively mitigate the seismic response of the building complex.