• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.9
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• pp.2234-2241
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• 1993

The torque variation in drilling process represents the problems of the efficient and stable machining. In order to cope with them, the active control method is adopted to drill the workpiece under the constant cutting torque though the cutting stiffness of the workpiece or the diameter of the drill bit changes. The cutting process is modeled in the geometric viewpoint related with the feed and the number of cutting lips. And the dynamic model is approximated to the first order system for the purpose of control. The adaptive PI control is used in computer simulations and experiments. The results of the study show the validity of the drilling method with torque control.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.4
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• pp.33-42
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• 2010

The induction motor drive applied to field oriented control is widely used in industry applications. However, it is deceased performance and authenticity by saturation, temperature changing, disturbance and parameters changing because modeling of induction motor is nonlinear and complex. In order to control variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation, even under ideal field oriented conditions. This paper proposes self tuning PI controller based on fuzzy-neural network(FNN)-PI controller that is implemented using fuzzy control, neural network, and adaptive fuzzy controller(AFC). Also, this paper proposes estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FNN-PI, AFC and ANN controller. Also, this paper proposes the anlysis results to verify the effectiveness of controller.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.192-197
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• 2007

This paper presents Hybrid PI controller of IPMSM drive using fuzzy adaptive mechanism(FAM) control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, Hybrid PI controller proposes a new method based self tuning PI controller. Hybrid PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.71-77
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• 1998

In this Paper, the training principles and the control method of adaptive array antennas using the LMS and CMA algorithms for the $\pi$/4 QPSK signal is showed and the convergence characteristics, the adaptivity of directional pattern SINR and the replication of desired signal of adaptive arrays are compared and discussed each other. Computer simulation results showed that the SINR of LMS adaptive array was 13.8［dB］, and that of CMA was 12.8［dB］, and also the convergence characteristics of LMS was fast a little than that of CMA. The LMS adaptive array was also performed null point well for the interference signal direction than that of the CMA adaptive array.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.506-509
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• 1986

In this paper, the control law for the system that has the variation of moment of inertia is designed. The proposed method is that the control input is obtained by using optimal PI control and partial adaptive control. The partial adaptive control input is adjusted by estimating the variational quantity of moment of inertia. This result gives us significant improvement of tracking ability.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.403-405
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• 1999

The model reference adaptive control(MRAC) algorithm is applied to the speed control of an inverter driven permanent magnet brushless do motor MRAC is compared to a standard PI controller. Applying this algorithm has also been proved by simulations that quick speed response without over-shoot could be obtained for the motor system with variable parameters. Simulation results show that the adaptive controller is superior to the PI controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.697-702
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• 2004

In this paper, we proposed that the problem of controlling induction motor with magnetic saturation, is studied from an input-output feedback linearization with adaptive algorithm. is considered. An adaptive input-output feedback linearizing controller is considered under the assumption of known motor parameters and unknown load torque. In order to achieve the speed regulation with the consideration of improving power efficiency, rotor angular speed and flux amplitude tracking objectives are formulated. Simulation results are provided for illustration.

• Journal of Advanced Marine Engineering and Technology
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• v.3 no.1
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• pp.19-31
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• 1979

Recently the adaptive control system, which keeps the control system always optimal by adjusting the control parameters automatically according to the variations of the plant parameters, have become very important in the field of control engineering. The adaptive control systems are usally composed of the plant identification, the decision of the optimal control parameters, and the adjustment of the control parameters. This paper deals with a method of the adaptive control system when PI or PID controller is used in the feed back control system. Its controlled object (the plant) is assumed to be described by the transfer function of $\frac{ke^{-LS}}{1+TS}$ where k, T and L are steady state gain, time constant and pure dead time respectively, and their values are variable in accordance with the change of environmental circumstance. It has been known that a pseudo-random binary signal is quite effective for the measurement of an impulse response of a plant. In adaptive control systems, however, the impulse response itself is not appropriate to determine the control parameters. In this paper, the authors propose a method to estimate directly the parameters of the plant k, T and L by means of the correlation technique using 3 level M-sequence signal as a test signal. The authors also propose a method to determine the optimal parameters of the PI or PID controller in the sense of minimizing the square integral of the control error in the feed back control system, and the values of the optimal parameters are computed numerically for various values of T and L, and the results are examined and compared with those of the conventional methods. Finally the above-mentioned two methods are combined and an algorithm to struct an adaptive control system is suggested. The experiments for the indicial responses by means of both the model of the temperature control system using SCR actuater and the analog simulations have shown good results as expected, and the effectiveness of the proposed method is verified. The M-sequence generator and the time delay circuit, which are manufactured for the experiments, are operated in quite a good condition.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.103-107
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• 2009

PI controller is widely used as voltage control system of generator. However when a generator system has various characters of continuance, a new PI parameter decision for accurate control is a hard task as method of solving this problem, in this paper, the method to generator voltage control using Neural Network self adaptive control is presented. A property continuous feedback control gain of voltage control system is decided by a rule of delta learning. The function of proposed control method is verified by voltage control experiment results of DC generator.

• 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.