• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.166-172
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• 1998

PD 제어기는 산업현장에 가장 널리 운영되는 제어알고리즘이지만 지금까지 보편적으로 사용되고 있는 PID 파라메터 동조방법인 Ziegler-Nichols 동조법으로는 화학공정 같은 비선형 특성이 크거나, 시정수가 큰 플래트에서는 좋은 성능을 얻을 수 없다. 본 논문에서는 릴레이 동조 실험을 통하여 임계 이득과 발진주기를 구하고, 이 값들로부터 Z-N 동조법을 적용하여 초기 동조값을 구한다. 이 값에 의해서 얻어진 공정 출력의 오차와 오차변화율을 입력으로 한 퍼지 동조기를 통하여 PID 제어기의 비례이득과 적분시간을 구하는 동조 방법을 제시한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.64-72
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• 1995

This paper proposes how to tune the gains of PI controllers in case of gain change in a process control system. Controllers of PI type have been used in industry and the gains of the controllers have been tuned by expert engineers. It, therefore, takes much time and efforts to tune the controllers. It is more difficult to find gains of multi-loop processes. The tuning method of a fuzzy tuner in this paper is developed based on the assumptions that the PI controllers are of analog type and are tuned off-line, and that the characteristic values must be supplied for the tuner. A Tuner using Fuzzy Logic(FLT1 is capable of showing presentlpast states of a process control system and finding gains of PI controllers. The verfication of the FLT is shown by various experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.395-407
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• 2006

본 논문에서는 설계변수와 제어기 이득의 자기 동조를 사용하는 PI+D 제어기 설계에 대하여 기술한다. 사용된 퍼지 PI+D 제어기는 일반적인 연속 시간 선형 PI+D 제어기를 근사화하여 사용하였고, 퍼지화는 퍼지싱글톤으로, 비퍼지화는 간략화된 무게중심법을 사용하였다. 제안된 제어기는 제어대상이 비선형일 때 자기 동조 성능이 개선된다. 퍼지 PI+D 제어기가 적용되면, 퍼지추정 결과는 분리된 퍼지 변수로서 다른 작용 성분으로 계산되고, 그 결과는 설계변수에 해당하는 함수의 형태로 결정되어 제어이득을 결정한다. 따라서 제안된 방법은 빠른 속도 추정의 성능을 가지며, 퍼지 입력변수의 증가에도 쉽게 적용될 수 있고, 재생 오차를 줄이는 이점을 가진다. 이 제어기는 설계변수와 제어기 이득의 사용으로 보다 높은 효율성과 개선점을 가지고 있다.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.388-398
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• 1998

In constructing fuzzy control systems. there are many parameters such as rule base. membership functions. inference m method. defuzzification. and I/O scaling factors. To control the system in properly using fuzzy logic. we have to consider t the correlation with those parameters. This paper deals with self-tuning of fuzzy control systems. The fuzzy controller h has parameters that are input and output scaling factors to effect control output. And we propose the looklongleftarrowup table b based self-tuning fuzy controller. We propose the PMTM(Plus-Minus Tuning Method) for self tuning method, self-tuning the initial look-up table to the appropriate table by adding and subtracting the values.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.355-367
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• 2007

This paper proposes a design method of the PI(Proportional-Integral)+D(Derivative) controller using self-tuning of the design variables and controller gains. The used fuzzy PI+D controller is the approximated conventional continuos time linear PI+D controller and the used fuzzification method is the fuzzy single tone and the adapted defuzzification method is the simplified tenter of gravity. Fuzzy estimation result would be calculated in the other function elements from the classified fuzzy variables and the result determined by the design variables decides the controller gains. As a result, the proposed method shows the capability of the high speed tuning and can be applied to the case of input variables with many fuzzy partitions and also can bring out the advantage to reduce the reconstruction(digital sampling reconstruction) error. Most simulation results show that this controller makes much bettor efficiency and improvement by using design variables and controller gains.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.120-125
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• 2005

In this paper, We propose the fuzzy controller for the gain tuning of PID controller The proposed controller doesn't use the crisp output error and rule tables though with a fuzzy inference process in forward fuzzifier, New Fuzzy PID Controller assigns relations and ranges of two variables of PID gain parameters. These new gain parameters are calculated by the fuzzy inference with max-min ranges of Kp and Kd. The Ki parameter is computed automatically between Kp and Kd parameter Is calculated by Ziegler-Nickels tuning rules. Finally we experimented the propose controller by the hydraulic servo motor control system. We can obtained desired results through the good control characteristics.

• 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 Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.10 no.1
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• pp.40-45
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• 1996

본 연구는 공정제어를 위한 복합형 퍼지-PID 제어기의 개발에 관한 것이다. 제안된 복합형 퍼지-PID제어기는 퍼지 규칙을 기반으로 한 이득 결정부분({{{{ { K}_{p } { K}_{d } }}}})과 고정이득({{{{ { K}_{i } }}}})을 합친 제어기이다. 모의 실험 결과 제안된 제어기는 고정된 파라메터를 갖는 전통 PID 제어기에 비해 더욱 양호한 제어성능을 나타내었다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.473-479
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• 2016

This paper describes an accurate and stable current control method of switched reluctance motors(SRMs), which have recently attracted considerable wide attention owing to their favorable features, such as high performance, high durability, structural simplicity, low cost, etc. In most cases, the PI controllers(PICC) have been used mostly for the current control of electric motors because their algorithm and selection of controller gain are relatively simpler compared to other controllers. On the other hand, the PI controller requires an adjustment of the controller gains for each operating point when nonlinear system parameters change rapidly. This paper presents a stable current control method of an SRM using self-tuning fuzzy current controller(STFCC) under nonlinear parameter variation. The performance of the considered method is validated via a dynamic simulation of the current controlled SRM drive using Matlab/Simulink program.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.19-24
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• 2007

In this paper, we propose a tuning method of PID-PD controller to satisfy design specifications in frequency domain as well as time domain. The proposed tuning method of PID-PD controller consists of the convex set of PID and PI-PD controller. PID-PD controller controls the closed-loop response to be located between the step responses, and Bode magnitudes of closed-loop transfer functions controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost function subject to sensor noise insensitivity and robust stability. Its effectiveness is examined by the case study and analysis.