• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.15-18
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• 2004

본 논문에서는 표면 부착형 영구자석형 동기 전동기(SPMSM)의 가감속과 부하 변동에 따른 속도 특성 향상을 위해 실제 속도와 부하 토크 관측기를 통한 부하 토크를 입력 변수로 설정하여 가변 이득 조절 알고리즘을 제안한다. 제안된 알고리즘을 증명하기 위해 여러 운전 조건에서 기존의 이득 시스템과 가변 이득 조절 시스템을 비교하여 제안된 알고리즘의 효용성을 검증하였다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.7
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• pp.65-73
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• 2006

This paper presents speed control of IPMSM drive using neural network(NN) PI controller. 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 of fixed gain PI controller, NNPI controller proposes a new method based neural network. NNPI controller is developed to minimize overshoot rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed 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 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.10
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• pp.1104-1111
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• 2003

The paper presents an algorithm for the compensation of gain and phase imbalances to exist between I-phase and Q-phase signal at direct conversion receiver. We propose a gain and phase imbalances blind equalization compensation algorithm by using variable step-size adaptive loop at direct conversion receiver. The blind equalization schemes have trade-off between convergence speed and jitter effect for the compensation of gain and phase imbalance. We propose the variable step-size adaptive loop method, which varies the loop coefficients according to errors, for recovering these problem. By using variable step-size adaptive loops, we propose to speed up the convergence process and reduce the jitter effect and simulation results show that the algorithm compensates signal loss and speeds up convergence time.

• 전기의세계
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• v.36 no.9
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• pp.658-664
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• 1987

최적이득을 구하는 해석적인 방식으로 안정여유에 의한 최적화방식과 공액경사법에 의한 최적화방식을 살펴보았으며, 두방식을 비교해 보면 몇몇 문제점이 존재하나 다음의 몇가지 점에서 공액경사법에 의한 최적화방식이 더 우수하다는 것을 알 수 있다. 1) 제어루우프내의 제어기 수에 관계없이 이 방식을 쉽게 적용할 수 있다. 2) 시스템을 수식으로 모델링할 때 거의 간략화함이 없이 표현하므로 실제 시스템과의 오차를 줄일 수 있다. 3) 평가함수 내의 가중치를 조정하여 원하는 과도응답을 가지는 최적이득으로 유도할 수 있다. 공액경사법에 의한 최적화방식은 벡터제어나 전류제어PWM등 보다 복잡한 제어루우프에도 쉽게 적용시킬 수 있으며 직류기 및 서보전동기의 속도 및 위치 제어시스템에도 적용이 가능하다.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.6
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• pp.602-611
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• 2004

Servo system has commonly adapted PI controller with fixed gains, because of its simplicity and determinative relationship among the parameters. The fixed gains PI system may be applied well to some operation conditions, but not non-linearities, complex and time variant operation conditions. For solving these problems, another conventional method, 'variable gun schedule according to speed', is published. The value of gain is determined according to the absolute value of the mover real speed. In this paper, FSTPIC(Fuzzy Self-Tuning PI Controller) is proposed based on various experiences to rapidly reduce speed error and to secure a good speed response characteristics. The effectiveness of proposed algorithms is demonstrated by comparing to two conventional gain systems via 4-quadrant operation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.24-31
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• 2007

This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. 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 of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed 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 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.9
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• pp.2349-2354
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• 1996

Convergence analysis on Godard's quartic (GQ) algorithm used forblind equalization is accomplished in this paper. The first main result is an explanation of the lacal behavior of the GQ algorithm around the global minimum point of the average performance functio, from which we can determine the adaptation gain. It is show that the normalized adaptation gain of the GQ algorithm should be smaller than that of the decision directed (DD) algorithm. In addition, it is observed that the GQ algorithm converges faster than the DD equalization algorithm.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.36-45
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• 1998

In this paper, a method of on-line PI gain-tuninng is proposed for the speed control of brushless D.C. motor by investigating the pattern of input and output without estimating parameter. Proportional gain is tuned in the process to obtain a fast speed response by supplying the maximum constant input. And integral gain is appropriately tuned in the process of proportional control so that the response may be stably converged and the overshoot may be prevented. Therefore because both control and gain-tuning are executed concurrently, additional works that estimate parameters and so on aren't required in the proposed method. In the proposed method, both fast-response and overshoot problem are well solved, and it is more useful and convenient than existing auto-tuning methods in the speed control of D.C. motor. It is illustrated by simulations and experimental results that the proposed method is useful and stable.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.1976-1988
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• 1996

This paper describes TCM(trellis coded modulation) schemes using 32VSB signal for digital CATV system. First we design optimum encoder with code rate 4/5 for 32VSB by using one dimenstional signal constellation and obtain 0.75-4.38 dB coding gains over the existing uncoded 16VSB. Second by using two dimensional signal constellation we design TCM encoders with code rate 9/10, which are better in the power efficienty (0.5-2.27 dB) and the transmission rate(12.5%), and we also design TCM encoders which have more coding gains than one dimensional TCM encoders for the larger number of states(more than 8 states).

• Proceedings of the KIPE Conference
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• 2013.11a
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• pp.179-181
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• 2013

일반적인 전동기 구동에 있어서 부하의 변화에 의해 관성이 변하는 경우 동일 속도 제어기 이득에서의 속도 응답은 오버슈트가 생기거나 진동하는 문제점이 있다. 따라서 정확한 속도제어가 필요한 응용분야에서 전동기의 관성 추정은 필수이다. 본 논문에서는 MRAS 관측기를 활용하여 영구자석동기전동기의 관성을 추정하고 추정된 관성으로 속도제어기의 제어이득을 선정할 경우의 속도 응답특성을 비교한다.