• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1560-1564
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• 2008

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID controller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. In this paper, PID-Self Tuning control method for motor control system as a compensation method solving this problem is presented. If the PID control system is stable in the sense that the error is inside the constraint set, the supervisory control is idle. If the error hits the boundary of the constraint, the supervisory controller begins operation to force the error back to the constraint set. We prove that the PID-Self Tuning control system is globally stable in the sense that the error is guaranteed to be within the tolerance limits specified by the system designer.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.75-79
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• 2002

본 논문에서는 선박 디젤엔진의 속도를 조절함에 있어서 환경 변화에서도 지속적으로 만족스러운 성능을 유지하도록 시스템 파라미터 추정자, 제어기 계수 수정자를 결합한 자기동조 PID 제어기를 설계한다. 유전알고리즘을 기반으로 한 온라인 추정자가 시스템의 파라미터를 추정하면, 제어기 계수 수정자는 제안한 동조규칙으로 계수를 조정하게 된다. 이를 위해 시스템을 시간지연 1차 모델로 근사화하여 유전알고리즘 기반으로 그 파라미터를 온라인 추정하는 문제를 다룬다. 제안한 방법의 성능은 B&W사의 4L80MC 디젤엔진을 제어대상으로 퍼지모델을 얻고 모의실험을 통하여 확인한다.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.139-147
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• 1996

PID control has been widely used for real control systems. Particularly, there are many researches on control schemes of tuning PID gains. However, to the best of our knowledge, there is no result for discrete-time systems with unknown time-delay and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown papameters and unknown time-delay system. A numerical simulation was presented to illustrate the effectiveness of this method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.1-10
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• 2007

This paper presents a direct nonlinear multivariable self-tuning PID controller using neural network which adapts to the changing parameters of the nonlinear multivariable system with noises and time delays. The nonlinear multivariable system is divided linear part and nonlinear part. The linear controller are used the self-tuning PID controller that can combine the simple structure of a PID controllers with the characteristics of a self-tuning controller, which can adapt to changes in the environment. The linear controller parameters are obtained by the recursive least square. And the nonlinear controller parameters are achieved the through the Back-propagation neural network. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation results are presented to adapt the nonlinear multivariable system with noises and time delays and with changed system parameter after a constant time. The proposed PID type nonlinear multivariable self-tuning method using neural network is effective compared with the conventional direct multivariable adaptive controller using neural network.

• ETRI Journal
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• v.10 no.4
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• pp.33-39
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• 1988

본 고는 자기동조 제어기 구성에 관한 논문으로 제어기는 공정의 매개변수 변화와 외란, 잡음에 대하여 운용자의 조작없이 스스로 제어 특성을 만족하도록 동작하며, 공장자동화 시스팀의 일부로서 계층제어 시스팀 구성이 가능한 통신기능을 가지고 있다. 또한, 공정의 시간지연, 불감시간, 비선형 등에 대해서 만족할만한 제어효과를 나타내며, 범용자기동조 제어모드와 PID제어모드를 갖는다. 본문에서는 자기동조 제어기의 시스팀구성, 하드웨어구성, 소프트웨어구성에 대하여 기술한다.

• 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.

• 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.

• 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.

• 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.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.66-68
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• 2004

PID제어기를 플랜트 파라미터를 이용하여 구성하는 IMC-PID제어에 대해 연구한다. 특히 변하는 플랜트에 대해서는 자기동조(ST, Self-Tuning)를 사용하여 시스템을 식별하여 활용한다. 특히 실시간으로 개루프의 위상여유 및 이득여유를 모니터링하여 정해진 구역을 벗어나게 되면 식별된 시스템파라미터를 이용하여 IMC-PID제어기를 구성한다. 또 시간영역 지표로 과도한 오차가 발생하는 경우에도 제어기를 갱신함으로서 전체적으로 보면 견실 PID제어기 형태를 갖게 한다.