• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.74-79
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• 2002

Many control techniques have been proposed in order to improve the control performance in discrete-time domain control system. In control system using these techniques, the response-characteristic of system is dependent on the gains of the controller. Specially, There is a need to readjust the gain of controller when the response of system is changed by disturbance or load fluctuation. In this paper, I-PD controller and pre-compensator are designed by multilayer neural network. The gains of I-PD controller and pre-compensator are adjusted automatically by back propagation algorithm when the response characteristic of system is changed under a condition. Applying this control technique to the position control system using a DC servo motor as a driver, the control performance of controller is verified by the results of experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.959-965
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• 2019

In this paper, we design a low noise amplifier to support ka-band satellite communication systems using 65-nm RFCMOS process. The proposed low noise amplifier is designed with high-gain mode and low-gain mode, and is designed to control the gain according to the magnitude of the input signal. In order to reduce the power consumption, the supply voltage of the entire circuit is limited to 1 V or less. We proposed the gain control circuit that consists of the inverter structure. The 3D EM simulator is used to reduce the size of the circuit. The size of the designed amplifier including pad is $0.33mm^2$. The fabricated amplifier has a -7 dB gain control range in 3 dB bandwidth and the reflection coefficient is less than -6 dB in high gain mode and less than -15 dB in low gain mode.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.688-697
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• 2017

It is very difficult to solve mathematically the optimal control problem for non - linear mobile robots to move to target points with minimum energy related to velocity, acceleration and angular velocity in minimum time. This paper proposes a method to obtain optimal control gains with which mobile robots move with minimum energy related to velocity, acceleration and angular velocity in minimum time using genetic algorithms. Mobile robots are non - linear systems so that their optimal control gains depend on initial positions. Hence initial positions are divided into some partition points and optimal control gains are obtained at each partition point with genetical algorithms. These optimal control gains are used to train neural networks that generate proper control gains at arbitrary initial position. Finally computer simulation studies have been conducted to verify the effectiveness of the method proposed in this paper.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.1-5
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• 2010

We propose an algorithm which can classify the system should use a PI controller, which have a weak high frequency attenuation characteristics near the critical frequency. To classify the system, we use a time delay element to calculate a gain attenuation rate near the critical frequency. The proposed algorithm also can design PI controller with the given magnitude margin and phase margin specification. The proposed algorithm uses time delay element and saturation function to identify the one point information in frequency domain. We justify the proposed algorithm via the simulation.

• Aerospace Engineering and Technology
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• v.7 no.1
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• pp.61-67
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• 2008

To design flight control law of an unmanned aerial vehicle, automated control gain determination program was developed. The procedure for determination of control gain was formulated as the control gains were designed from the optimal solutions of the optimization problem. PSO algorithm, which is one of the evolutionary computation method, and SQP algorithm, which is one of the nonlinear programming method, are used as optimization problem solver. Thru this technique, computation time required for finding the optimal solution is decreased to 1/5 of that of PSO algorithm and more accurate optimal solution is obtained.

• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.39-43
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• 2016

In this paper, we propose PID gain auto tuning method in steering type mobile robot. PID controller gain select method are various methods. Ziegler-Nichols step tuning method is one method tuning in PID controller. Use step tuning method find a the first gain and did experiment in steering mobile robot. and Make a new the second gains from the first gains. After appling the second gain in PID controller, Where perform observe for convergence time and stabilization error. Experiments result the second gain are useful in real steering mobile robot system.

• 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.

• Proceedings of the KIPE Conference
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• 2008.10a
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• pp.202-205
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• 2008

본 논문은 이중여자 발전기를 사용하는 풍력발전기에서 안정적인 계통투입을 위한 계통연계 전 후 발전기의 인덕턴스 변화에 따른 전류제어기 이득 값 선정에 대하여 연구하였다. DFIG(Doubly Fed Induction Generator)방식을 이용하는 풍력발전기는 회전자 전류제어를 함으로써 고정자의 전압을 제어하고, 제어된 고정자 전압은 계통과 연결된다. 특히 회전자 전류제어기 성능은 LVRT(Low Voltage Ride Through)등 예상하지 않은 외란에 대하여 빠른 응답성을 필요로 한다. 그러나 발전기가 계통과 연계되는 순간 발전기의 내부 파라미터 값의 변동이 발생하며, 이는 계통 투입 전 발전기 파라미터에 근거한 RSC(Rotor Side Converter)측 전류제어기 이득 값에 영향을 미쳐, 전류제어가 불안정하게 하는 원인이 되거나, 전류제어 응답성을 낮추게 하는 요인이 된다. 따라서, 본 연구에서는 계통투입 전 후의 RSC측 전류제어기의 이득 값을 달리하여 안정적인 계통 투입이 가능하도록 하는 알고리즘을 시뮬레이션과 실험으로 증명하였다.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.354-359
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• 1989

음 함수(implicit function)의 미분관계를 고려하여, 유도한 본 연구의 판별기준을 통해 조작변수들과 제어변수들간의 pairing을 합리적으로 정할 수 있었으며, 기존의 기준이 해석하지 못한 대각선 이득에 대한 대각선에 있지 않은 이득의 영향을 효과적으로 고려할 수 있었다. 그리고 여러 경우에 대해 적응 예제들을 통하여 제시한 기준의 검증과 응용성을 알아보았다.