• 전력전자학회논문지
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• 제3권3호
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• pp.173-183
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• 1998

본 논문은 신경회로망에 의한 퍼지제어기의 소속함수를 자동동조하는 방법을 제시하였다. 신경회로망 에뮬레이터는 퍼지제어기의 소속함수와 퍼지규칙을 재구성하는 경로를 제공하며, 재구성된 퍼지제어기는 유도전동기의 속도제어를 위해 사용한다. 따라서, 연산 시간과 시스템 성능의 관점에서 제안된 방법은 전동기 상수가 변동될 시에도 기존의 제어 방식보다 우수하다. 공간전압벡터 PWM 발생을 위한 고속연산을 수행하고 자기학습형 퍼지제어기 알고리즘을 구현하기 위해서 32비트 마이크로프로세서인 DSP(TMS320C31)을 사용하였다. 컴퓨터 시뮬레이션과 실험 결과를 통하여, 제안된 방식이 PI 제어기나 기존의 퍼지제어기보다 향상된 제어 성능을 보일 수 있음을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.700-702
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. In fuzzy controller which has been widely applied and used. in order to construct the best fuzzy rules that include adjustment of fuzzy sets, a highly skilled techniques using trial and error are required. To deal with such a problem, first, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller from each control output in steady state and transient state. Second, a auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller, utilizing the simplified reasoning method and genetic algorithms. In addition, to obtain scaling factors and PID Parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The HFCs are applied to the first-order second-order process with time-delay and DC motor Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed from performance indices.

• Transactions on Control, Automation and Systems Engineering
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• 제1권2호
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• pp.94-98
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• 1999

Optical scanning systems use glavanometers to point the laser beam to the desired position on the workpiece. The angular speed of a galvanometer is typically controlled using Proportional+Integral+Derivative(PID) control algorithms. However, natural variations in the dynamics of different galvanometers due to manufacturing, aging, and environmental factors(i.e., process uncertainty) impose a hard limit on the bandwidth of the galvanometer control system. In general, the control bandwidth translates directly into efficiency of the system response. Since the optical scanning system must have rapid response, the higher control bandwidth is required. Auto-tuning PID algorithms have been accepted in this area since they could overcome some of the problems related to process uncertainty. However, when the galvanometer is attached to a larger mechanical system, the combined dynamics often exhibit resonances. It is well understood that PId algorithms may not have the capacity to increase the control bandwidth in the face of such resonances. This paper compares the achieable performance and robustness of a galvanometer control system using a PID controller tuned by the Ziegler-Nichols method and a controller designed by the Quantitative Feedback Theory(QFT) method. The results clearly indicate that-in contrast to PID designs-QFT can deliver a single, fixed controller which will supply high bandwidth design even when the dynamics is uncertain and includes mechanical resonances.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.794-796
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• 1999

본 논문에서는 3상 유도전동기의 속도를 제어하는데 기존 제어기의 문제점을 해결하고 최적화하기 위해서 유전자 알고리즘을 이용한 하이브리드 퍼지 -PID(HFPID) 제어기를 고안하고, 이에 대한 파라미터 설정 방법을 제안한다. 유도전동기의 제어는 지연시간이 길고, 비선형성이 강하며, 부하변동이 잦은 프로세스이기 때문에, 기존의 제어방식으로는 만족할만한 결과를 얻을 수 없다. 제안한 하이브리드 퍼지-PID 제어기는 PID 제어기의 장점인 과도기의 우수성과 퍼지 제어기의 장점인 정상기의 우수성을 퍼지 변수로 결합시켜 설계한다. 이 제어기에 유전자 알고리즘을 적용하여 최적의 퍼지 및 PID 파라미터를 설정하다. 그리고 이 제어기를 3상 유도전동기의 속도 제어에 응용한다. 또한 속도오차에 대한 룩업 표를 만들어 온라인 실시간 제어를 가능하게 한다. 이상의 과정을 3상 유도전동기에서 컴퓨터 시뮬레이션 하였다. 시뮬레이션 결과를 비교해 볼 때, 하이브리드 퍼지-PID 제어기는 기존의 제어기 보다 전동기의 속도 및 토크성분 전류 둥의 특성에서 우수한 성능을 보였다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제15권5호
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• pp.470-475
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• 2015

This paper presents a wideband Current-Reused Voltage Controlled Oscillator (VCO) with 2-Step Automatic Amplitude Calibration (AAC). Tuning range of the proposed VCO is from 1.95 GHz to 3.15 GHz. The mismatch of differential voltage is within 0.6 %. At 2.423 GHz, the phase noise is -116.3 dBc/Hz at the 1 MHz offset frequency with the current consumption of 2.6 mA. The VCO is implemented $0.13{\mu}m$ CMOS technology. The layout size is $720{\times}580{\mu}m^2$.

• Journal of Mechanical Science and Technology
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• 제19권2호
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• pp.505-519
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• 2005

In this paper, we develop an anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2 DOF PID controller. The simulation and experimental results show that the proposed control scheme guarantees performances, trolley position, sway angle and settling time in NNP PID controller than other controller. As the results in this paper, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard. Accordingly, the proposed algorithm in this study can be readily used for industrial applications.

• 전자공학회논문지SC
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• 제46권3호
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• pp.8-14
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• 2009

본 논문은 성능 향상을 위하여 IMC 제어 구조를 갖는 PID 제어기 설계를 제안했다. 내부 모델은 최종값 정리와 유전자 알고리즘을 이용하여 2차의 지연시간을 갖는 모델로 동정 하였다. 그리고 제어기 파라미터 값은 성능지수 (IAE, ITAE)값이 최소가 되도록 내부 모델과 수치적 계산에 의해서 자동 동조된다. 시뮬레이션을 통하여 다양한 공정에 대하여 본 논문에서 새롭게 제안된 방법이 기존의 방법보다 우수함을 확인 할 수 있었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.505-508
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• 1997

In this paper, an auto-tuning method for fuzzy controller based on the neural network is presented. The backpropagated error of neural emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and used for speed control of induction motor. For the torque control method, an indirect vector control scheme with slip calculation is used because of its stable characteristics regardless of speed. Motor input current is regulated by a current controlled voltage source PWM inverter using space voltage vector technique. Also, the scheme of current control fuzzy controller is synchronous reference frame with decoupling term. DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzz. control algorithm. An IPM is used to simplify hardware design.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.515-518
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• 1998

This paper proposes a new hybrid algorithm for auto-tuning fuzzy controllers improving the performance. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a genetic-MGM algorithm. The object of the proposed algorithm is to promote search efficiency by a genetic and modified gradient optimization techniques. The proposed genetic and MGM algorithm is based on both the standard genetic algorithm and a gradient method. If a maximum point don't be changed around an optimal value at the end of performance during given generation, the genetic-MGM algorithm searches for an optimal value using the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algorithms. Simulation results verify the validity of the presented method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2299-2301
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• 2000

In this paper, the design of PID controller using Neural networks for the control of non-linear system is presented. First, non-linear system is identified using BPN(Backpropagation Network) algorithm. This identified model is connected to the PID controller and the parameters of PID controller are updated to the direction of reducing the difference between the identified model output and model reference output in arbitrary input signal. Therefore, identified model output tracks the model reference output in an acceptable error range and the parameters of controller are updated adaptively. The output of the system has a good performance in case of both noisy and noiseless model reference and we can control the system stable in off-line when the dynamics of the system is changed.