• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.225-228
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• 2000

We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nickels method. So deciding binary strings of parents generation using by the fitness values of genetic algorithms, we perform selection, crossover and mutation to generate the descendant generation. The advantage of this method is better than the Ziegler-Nickels method in characteristic of output, and has extent of applying without limit of K, L, T parameters.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1113-1115
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• 1996

The servo system requires faster and more accurate dynamic responses. A new technique for the position control of DC servo motors is presented in this paper. The proposed technique employs a Self Tuning Regulator Proportional Integral Derivative(STR PID) position control systems in order to improve the dynamic performance of a DC servo motor. Recursive -least -squares (RLS) method is used in order to estimate the STR PID coefficients, $K_P$, $K_I$, and $K_D$. In order to consider dynamics such as voltage, angular velocity, and rotor angle, the above method was applied position control system.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2218-2220
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• 2003

현대 산업현장에서 80%이상 사용되는 PID(proportional integral derivative) 제어기는 제어성, 적응성, 제어이득 조정 등의 특정이 있어나 제어 대상에 대한 PID 제어 계수를 경험적 방법인 수동으로 동조해야하는 문제점이 있다. 이를 개선하기 위해 본 논문에서 PID제어기의 최적 자동동조를 위한 릴레이 동조 방법을 제안한다. 기존의 한계감도법과 과도응답 법으로 초기계수를 결정하는 방법보다 유연성과 적용성이 높고, 이를 마이크로프로세서(DSP : TMS-320C32)에 적용하여 소프트웨어적으로 릴레이의 기능이 이루어지도록 설계했다. 이는 Ziegler-Nichols 계수조정법이 갖는 적용대상의 제약성을 극복한 방법이며, 릴레이에 의해 출력을 강제 진동시키고 출력의 진폭과 주기를 이용하여 PID 계수를 조정하고, 또 상대안정성의 척도인 위상여유를 고려하므로 시스템의 상대안정성과 견실성을 향상시킬 수 있음을 확인하였다.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.436-438
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• 1993

A rule based fuzzy expert system in self-tune PID controllers is presented in this paper. The rule base. the core of the expert system, is extracted from the Wills' tuning map and the author's knowledge about the implicit relations between PID gains and controlled output response. The overall control system consists of the relay feedback scheme and the expert system, where the one is responsible for initial tuning and the other for subsequent tuning. The PID control system with the proposed fuzzy expert system, shows better convergence rate and control performances than those of a Litt in spite of the fact that the two rule bases are extracted from the same maps provided by Wills.

• Journal of Korean Port Research
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• v.12 no.2
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• pp.217-224
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• 1998

During the operation of crane system in container yard, the objective is to transport the load to a goal position as quick as possible without rope oscillation. The container crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid transportation is required. Therefore, we developed an optimal controller which has to control the crane system with disturbances. In this paper, we present a design of optima 2-DOF PID controller for the control of gantry crane which has to control swing motion and trolley position. We used evolution strategy(ES) to tune the parameters of 2-DOF PID controller. It was compared with general PID controller. The computer simulations show that the proposed method has better performances than the other method.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.9-15
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• 1999

A piezoelectric actuator is widely used in precision positioning applications due to its excellent positioning resolution. However, the piezoelectric actuator lacks in repeatability because of its inherently high hysteresis characteristic between voltage and displacement. In this paper, a controller is proposed to compensate the hysteresis nonlinearity. The controller is composed of a PID and a neural network part in parallel manner. The output of the PID controller is used to teach the neural network controller by the unsupervised learning method. In addition, the PID controller stabilizes the piezoelectric actuator in the beginning of the learning process, when the neural network controller is not learned. However, after the learning process the piezoelectric actuator is mainly controlled by the neural netwok controller. In this paper, the excellent tracking performance of the proposed controller was verified by experiments and was compared with the classical PID controller.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.109-112
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• 2000

We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control In various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade -approximated, then initial values are determined by the Ziegler-Nichols method. After inputting constraints of evolution programs, we perform crossover and mutation to generate the descendant generation. The advantage of this method is better than the Ziegler-Nickels method in characteristic of output and has extent of applying without limit of K, L, T.

• 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 Korean Society for Precision Engineering
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• v.15 no.8
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• pp.126-134
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• 1998

본 연구에서는 회전운동을 제어하기 위한 새로운 작동기로서 전기장에 대하여 매우 빠른 응답특성을 갖고 있는 두 쌍의 실린더형 ER(electro-rheological) 클러치/브레이크 작동기를 제안하였다. 자체조성 된 ER유체의 빙햄특성 모델을 실험적으로 도출하였으며, 이와 연계한 작동기 모델을 구성하여 전기장에 따른 전달 및 제동 토크를 해석한 후 알맞은 크기의 클러치/브레이크 작동기를 제작하였다. 제작된 작동기의 동적특성(시상수 등)을 작동기 모델에 고려하기 위하여 계단입력 전기장에 따른 과도응답 실험을 클러치와 브레이크 모드에서 각각 수행하였다. 제안된 작동기의 응용성을 보이기 위하여 두쌍의 작동기로 구동되는 실험실 차원의 소형 와권식 세탁기 시스템을 구성한 후 동적지배방정식을 유도하다. 각 작동기와 연계된 PID제어기를 설계하여 세탁과 탈수시의 회전운동을 제어하였으며, 부하질량의 변화에 대한 작동기 시스템의 제어 효율성과 장시간 운전을 통한 제어 내구성 실험을 수행하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.2
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• pp.84-91
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• 2005

For long time, the takeoff and landing control of airship was worked by human handling. With the development of the autonomous control system, the exact controls during the takeoff and landing were required and lots of methods and algorithms were suggested. This paper presents the result of airship take-off and landing by buoyancy control using air ballonet volume change and performance control of pitch angle for stable flight within the desired altitude. For the complexity of airship's dynamics, firstly, simple PID controller was applied. Due to the various atmospheric conditions, this controller didn't give satisfactory results. Therefore, new control method was designed to reduce rapidly the error between designed trajectory and actual trajectory by learning algorithm using an artificial neural network. Generally, ANN has various weaknesses such as large training time, selection of neuron and hidden layer numbers required to deal with complex problem. To overcome these drawbacks, in this paper, the RBFN (radial basis function network) controller developed. The weight value of RBFN is acquired by learning which to reduce the error between desired input output through and airship dynamics to impress the disturbance. As a result of simulation, the controller using the RBFN is superior to PID controller which maximum error is 15M.