• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.22-33
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• 1999

This paper presents the method for the automatic tuning of a design weighting polynomial parameters of a generalized minimum-variance stochastic ultivariable self-tuning controller which adapts to changes in the higher order nonminimum phase system parameters with time delays and noises. The self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing the design weighting polynomial parameters of the controller. The proposed multivariable self-tuning method is simple and effective compared with pole restriction method. The computer simulation results are presented to adapt the higher order multivariable system with nonminimum phase and with changeable system parameters.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.4
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• pp.264-274
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• 2003

This paper presents a direct generalized minimum-variance self tuning controller with a PID structure using neural network which adapts to the changing parameters of the nonlinear system with nonminimum phase behavior, noises and time delays. The self-tuning controller with a PID structure is a combination of the simple structure of a PID controller and the characteristics of a self-tuning controller that can adapt to changes in the environment. The self-tuning control effect is achieved through the RLS (recursive least square) algorithm at the parameter estimation stage as well as through the Robbins-Monro algorithm at the stage of optimizing the design parameter of the controller. The neural network control effect which compensates for nonlinear factor is obtained from the learning algorithm which the learning error between the filtered reference and the auxiliary output of plant becomes zero. Computer simulation has shown that the proposed method works effectively on the nonlinear nonminimum phase system with time delays and changed system parameter.

• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.497-505
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• 2000

퍼지 논리 제어기(FLC)는 복잡한 프로세스와 비선형 프로세스와 비선형 프로세스에 사용되기 위해 연구되어져왔다. PI형 퍼지 제어기는 가장 보편적이고 실용적이다. 그러나 종래의 PI형 퍼지 제어기들은 큰 불감대를 가진 시스템이나 비선형 시스템에 대해 큰 오버슛과 과도한 발진으로 인해 불안정하다. 본 논문에서는 PI형 퍼지 제어기에서 제어 입력의 축적에 의해 야기된 오버슛을 제거하기 위한 관점에서, 두 개의 퍼지 제어기를 사용하여 좋은 성능을 이루기 위해, 직접적인 성능치로부터가 아니라, 현재의 프로세스 경향에만 의존하여, 조정하는 제어동작들을 발생하는 자기 동조 메카니즘을 사용하였다. 시뮬레이션 결과, 비선형 프로세스뿐만 아니라 선형의 다양한 형태를 갖는 프로세스에서 제안된 PI형 퍼지 제어기가 종래의 제어기의 성능을 능가한다는 것을 보여준다.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.826-827
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• 2015

본 논문은 비선형적인 파라미터 특성을 갖는 Switched Reluctance Motor(SRM)의 강인제어를 위한 보다 정확하고 안정적인 전류제어 방법에 대해 설명한다. 기존의 전류제어 방법에는 이득설정이 간편한 PI 제어기를 이용한 방법이 주로 사용되어왔다. 본 논문에서는 자기동조 퍼지 제어기를 이용한 방법과 Dead-Beat 제어기를 이용한 방법을 통하여 파라미터의 변화에도 안정적인 전류제어가 가능한 것을 보였고 PI 전류 제어기와 자기동조 퍼지 전류 제어기, 그리고 Dead-Beat 전류 제어기를 각각 적용한 전류제어 SRM 드라이브의 Matlab/Simulink 시뮬레이션 결과를 통하여 제어성능을 비교분석하였다.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.160-168
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• 1997

A $H_{\infty}$self-tuning control scheme for the tip position of a flexible link robot handling unknown loads is presented here. The scheme essentially comprises a recursive least-squares identification algorithm and $H_{\infty}$self-tunning controller. The $H_{\infty}$control low is designed to be robust to uncertain parameters and the self-tunning action provides adaption to unknown parameters. Through numerical study, the performance comparison of the $H_{\infty}$self-tuning controller with a constant gain $H_{\infty}$controller as well as a LQG self-tuning controller clearly shows its superior ability in handling load changes in quiescent states.nt states.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.80-83
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• 2002

정밀한 서보기술에 바탕을 두고 있는 산업용 로봇 팔은 기계적인 강성도와 서보기구들로 인하여 정확한 제어가 가능하다 그러나 로봇팔은 동작중비 관성모멘트의 변화와 기하학적인 구조로 인하여 비선형적인 시스템이다. 특히 관성모멘트의 변화는 로봇팔의 회전속도와 로봇팔이 이동시키는 대상물의 무게 등에 따라 관성모멘트는 변할 수 있다. 이로 인하여 관성모멘트의 변화에 따라 로봇팔의 정확한 위치제어가 힘들어진다. 따라서 본 논문에서는 관성모멘트의 변화에도 불구하고 강인한 응답특성을 나타내는 제어기의 설계가 요구된다. 일반적으로 PID .제어기는 설계의 용이성으로 산업현장에서 널리 사용된다. 그러나 PIB 제어기의 각 계수값을 설정하는데 많은 어려움이 발생한다. 따라서 본 논문에서는 PID 제어기의 각 계수 값을 퍼지알고리즘을 이용하여 자동으로 설계할 수 있는 자기동조 PID 제어기를 설계한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.8
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• pp.708-714
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• 1990

This paper has proposed a self-tuning controller for tracking reference trajectory by measuring End-point of arm on robot manipulator whose link is light and flexibls, and proved the perforformance of the algorithm proposed through the computer simulation. As an object of control, a flexible robot manipulator with two-links was selected. As for structure of model, it utilized an assume mode shape method with include travity force and derived a dynaics equation by adapting two kinds of vibration mode of each.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.348-354
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• 1999

In recent years, a PID controller has been used as a major control method in real control processes. This controller requires a determination of PID control gains. But it is difficult to select the best gains theoretically. Thus there have been many approaches to determine them empirically Most of them are based on experience and knowledge. In this paper, we proposed a tuning method of the PID Parameters by using neural network. To show effectiveness of the proposed method, the simulation of DC motor and one link manipulator position control is carried out.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.5
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• pp.29-38
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• 1998

This paper proposes the neural network self-tuning PID controller for the load frequency control of 2- areas power system, namely, the prompt convergence of frequency and tie-line power flow deviation. The neural network applied to computer simulation consists of neurons of two inputs, ten hiddens and tliree outputs layer. Neurons of two inputs layer receive the error and its change rate of the system and cutputs layer consists of three neurons for the parameters of the PID controller. The simulation results shows that the proposed neural network self-tuning PID controller is superior to conventional control t~:chniques(Optimal, PID) in dynamic response and control performance.