• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.79-81
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• 1987

Expert systems have a variety of potential applications in process control. The application domain ranges from the entire plant system to a single loop system. Both, off-line and real-time problems may be realized. In this paper, expert system is employed as a part of a single control loop of PID Controller with self-tuning. The goal of expert system in the present study is to build up the necessary process knowledge required for efficient control. In order to achieve this process, the development of an expert system and a prototype model is carried out. OPS5, a rule based production system, is utilized in experiment, and common LISP is used for man-machine interface.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.19-26
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• 1998

In this paper, Simulation result was studied by PID controller in series to the estblised neural networks controller. Neural network model is composed of two layers to evaluate tracking performance improvement. The regular dynamics was also studied for the expected error to be minimized by using Widrow-Hoff delta rule. As a result of the study, We identified that tracking performance improvement was developed more in case of connecting PID than conventional neural network controller and that tracking plant parameter in 251 sample was approached rapidly in case of time varying.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2501-2503
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• 2004

In this paper, we propose an auto-tuning control algorithm for a mobile robot. This controller consists of a three layer neural networks and a PID controller. In order to compensate for uncertainties from unknown dynamics and ignored dynamic effects such as slip conditions, neural network based position schemes are proposed. The results of simulations show the validity of proposed method. This controller learns quickly the model and has good position control performance.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2763-2765
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• 2003

Generally, we made use of PID control for torque control, speed control and stability, Hence, dynamic characteristic of DC motor has been studied for stable drive and accurate speed control by many engineers. But, in this paper, we applied genetic algorithm to current control for robust control and stability In conclusion, we prove that current control of genetic algorithm can be high efficiency.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.11
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• pp.1103-1109
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• 2009

In this paper, the control of a membrane used in reverse osmosis desalination plant by using immune algorithm(IA) is addressed. The proposed algorithm IA of auto tuning method can find optimal gains and compared with conventional Ziegler-Nichols tuning method. The results of computer simulation represent that the proposed IA shows a good control performances better than Ziegler-Nichols tuning method.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.346-350
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• 1989

This paper concerned about a study on the position control of KED-1 robot manipulator using PID self-tuning controller. For two joint manipulator KED-1, KED-1 manipulator is translated into kinematics to control each joints in joint space seheme. Angle displacements of joint coordinate are transformed into reference angle velocity of each subsystem through trajectory planning. Also, time sharing technique is used to control KED-1 manipulator. A series of simulation and experiment are performed for each joint in show the valid of proposed algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.9
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• pp.1463-1468
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• 2003

This paper presented the real-time self-tuning learning control based on evolutionary computation, which proves its superiority in finding of the optimal solution at the off-line learning method. The individuals of the populations are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations is proposed. It is possible to control the control object slightly varied as time changes. As the state value of the control object is generated, evolutionary strategy is applied each sampling time because the learning process of an estimation, selection, mutation is done in real-time. These algorithms can be applied; the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes.

• Proceedings of the KAIS Fall Conference
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• 2010.11a
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• pp.325-328
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• 2010

최근의 인터넷환경은 다양한 형태의 가상 및 원격 교육이 가능한 기반을 제공하고 있으며, 대학 및 교육기관에서는 이를 활용한 새로운 교육용 도구의 개발이 활발히 이루어지고 있다. 본 논문은 시공간의 제약 없이 실험을 수행할 수 있도록 하여 학습자들에게 반복 학습이 가능하도록 하였고, 유량제어를 실현 할 수 있는 비선형 시스템의 이중탱크 기구를 이용하여 다양한 제어이론을 실험할 수 있는 웹기반 실험실을 구현하였다. 전체 시스템은 SISO 시스템과 MIMO 시스템을 학습자가 선택하여 실험할 수 있도록 하였다. 유량제어 방식은 수동, PID, FUZZY 제어로 실험할 수 있도록 하여 학습자들에게 여러 가지 제어이론을 다양하게 학습할 수 있도록 구성하였으며, 릴레이 자기 동조법을 구현하여 학습자들로 하여금 PID변수를 확인할수 있도록 하였다. 또한 Web-Cam을 통하여 실험화면을 실시간으로 확인하면서 시뮬레이션을 동시에 실행하여 비교할 수 있도록 구현하였다.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.375-378
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• 1991

This paper presents a design method of synchronous generator excitation controller using self-tuning PID algorithm. Controller parameter is determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameter of controller. minimum variance algorithm using the recursive leastsquare(RLS) indentification method is adopted and the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping and conversion characteristics. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performances than conventional controller.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.509-511
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• 1998

Design of fuzzy logic controllers encounters difficulties in the selection of optimized membership function and fuzzy rule base, which is traditionally achieved by tedious trial-and-error process. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm(GA). The controller design space is coded in base-7 strings chromosomes, where each bit gene matches the 7 discrete fuzzy value. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a do-servo motor control system. It was presented in discrete fuzzy linguistic value, and used a membership function with Gaussian curve. The performance of this control system is demonstrated higher than that of a conventional PID controller and fuzzy logic controller(FLC).