• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.202-208
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• 2014

Friction force on robot systems is highly nonlinear and especially disturbs precise control of the robots at low speed. This paper deals with the dynamic friction compensation problem of a well-known one-link benchmark robot system. We consider the LuGre model because the model can successfully represent dynamic characteristics and various effects of friction phenomenon. The proposed controller is constructed as two parts. An adaptive controller based on dual observers is used to estimate and compensate the dynamic friction. In order to attenuate the friction estimation error and other disturbances, PI observer is additionally designed. Through the computer simulations with the benchmark system, this paper first examines the effects of nonlinear dynamic friction on the control performance of the benchmark robot system. Next, it is shown that the control performance against the dynamic friction is improved by using the proposed controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.408-411
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• 2009

In this paper, conventional PI, fuzzy neural network(FNN) and adaptive teaming mechanism(ALM)-FNN for rotor field oriented controlled(RFOC) induction motor are studied comparatively. The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. Comparative study of PI, FNN and ALM-FNN are carried out from various aspects which is dynamic performance, steady-state accuracy, parameter robustness and complementation etc. To have a clear view of the three techniques, a RFOC system based on a three level neutral point clamped inverter-fed induction motor drive is established in this paper. Each of the three control technique: PI, FNN and ALM-FNN, are used in the outer loops for rotor speed. The merit and drawbacks of each method are summarized in the conclusion part, which may a guideline for industry application.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.5
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• pp.25-31
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• 2007

This paper presents a comparison of different current controller response characteristics of SRM. The most common current controllers of the SRM is hysteresis type. The hysteresis controller is easy to implement and fast current control response, but has the inherent disadvantage of switching frequency variations. The other common type of current controller is PI scheme. The design of a classical PI current controller with fixed parameters for SRM is not an easy task due to the extreme nonlinear characteristics. In this paper, some linearization technique is used for design of PI current controller. Experimental results of 1-hp SRM are presented for the basic reference data which can be used to select the proper current control scheme according to the applications.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.4
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• pp.384-394
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• 2002

In this paper, a new control strategy is proposed to improve the quality of the welding products. The conventional nonlinear power control system of spot welders is linearized using nonlinear feedback linearization technique based on differential geometry theory. An evolution strategy(ES) geometry is used to find optimal gain of PI controllers. It tries to find out the optimal control parameters by imitating the natural evolution. Some Simulation and experimental results show that the proposed variable power control system using ES algorithm has better dynamic performances than the conventional one.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.247-248
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• 2012

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.2
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• pp.63-72
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• 1996

In order to regulate the cutting force at a desired level during peripheral end milling processes a feedrate override Adaptive Control Constraint (ACC) system was developed. The feedrate override function was accomplished through a development of programmable machine controller (PMC) interface technique on the NC controller, Nonlinear model of the cutting process was linearized as an adaptive model with a time varying process parameter. An integral type estimator was introduced for on-line estimation of the cutting process parameter, Zero order hold digital control methodology which uses pole-assignment concept for tuning of PI controllers was applied for the ACC system. Performance of the ACC system wsa confirmed on the vertical machining center equipped with fanuc OMC through a large amount of experiment.

• International Journal of Automotive Technology
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• v.8 no.1
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• pp.39-48
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• 2007

This paper addresses the problem of period and priority assignment in networked control systems (NCSs) using a fixed priority scheduler. The problem of assigning periods and priorities to tasks and messages is formulated as an optimization problem to allow for a systematic approach. The temporal characteristics of an NCS should be considered by defining an appropriate performance index (PI) which represents the temporal behavior of the NCS. In this study, the sum of the end-to-end response times required to process all I/Os with precedence relationships is defined as a PI. Constraints are derived from the task and message deadline requirements to guarantee schedulability. Genetic algorithms are used to solve this constrained optimization problem because the optimization formulation is discrete and nonlinear. By considering the effects of communication, an optimum set of periods and priorities can be holistically derived.

• Journal of Power Electronics
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• v.8 no.2
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• pp.141-147
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• 2008

This paper deals with a new and improved control technique for shunt active filters (AF) used for compensating unwanted harmonic currents injected in the mains due to nonlinear varying loads. This work is motivated by the need to find a permanent solution to the rigorous hit and trial method for evaluating system parameters in an indirect control of AF. A fuzzy pre-compensated PI (Proportional-Integral) controller is used to fuzzify the reference DC voltage of AF to the controller input so that the overshoots and undershoots in its DC link voltage are minimized and the settling time is improved. A three-phase diode rectifier with R-L (Resistive-Inductive) load is used as a non-linear load to study the effectiveness of the proposed controller of the AF. Robustness to filter parameter variations, insensitivity to controller parameter variations, and transient response has been taken as performance evaluation parameters. The results are shown through simulations in Matlab using power system block sets to demonstrate the capability of the proposed controller of the AF.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.4
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• pp.367-373
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• 2014

The most common current controller for the Switched Reluctance Motor (SRM) is the hysteresis controller. This method, however, suffers from such drawbacks as variable switching frequency, consequent audible noise and high current ripple. These disadvantages make this controlling method undesirable for many applications. The alternative solution is the PI controller. Since the fixed gain PI current controller can only be optimized for one operating point, and on the other hand, SR motor is highly nonlinear, PI controller gain should be adjusted according to incremental inductance. This paper presents a novel method for PI current controller gain adaptation which is simple and yields a good performance. The proposed controller has been implemented on a test bench using a eZdsp F28335 board. The performance of the current controller has been investigated in both simulation and experimental tests using a four-phase 8/6 4KW SRM drive system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.157-165
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• 2002

This paper presents the implementation of the speed control system for 3 phase induction motor using PD controller and neural networks. The PD controller is used to control the motor and to train neural networks at the first time. And neural networks are widely used as controllers because of a nonlinear mapping capability, we used feedforward neural networks(FNN) in order to simply design the speed control system of the 3 phase induction motor. Neural networks are tuned online using the speed reference, actual speed measured from an encoder and control input current to motor. PD controller and neural networks are applied to the speed control system for 3 phase induction motor, are compared with PI controller through computer simulation and experiment respectively. The results are illustrated that the output of the PD controller is decreased and feedforward neural networks act main controller, and the proposed hybrid controllers show better performance than the PI controller in abrupt load variation and the precise control is possible because the steady state error can be minimized by training neural networks.