• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2102-2104
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• 2001

This paper present the strategy of self-tuning nonlinear PID control using neural network. The nonlinear PID controller consists of a conventional PID controller and a neural network compensator. The neural network is trained by back-propagation algorithm. In this paper we propose modified back-propagation algorithm to improve learning speed. The results of simulation show the usefulness of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.211-214
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• 1997

This paper applies fuzzy self-tuning PID controller in DS/CDMA cellular system. Power control is essential in DS/CDMA to compensate for the differing received powers due to both the slowly varying long-term and fast varying short-term fading processes and co-channel interference. The controller proposed is adaptable for the variations of the system dynamics and especially for the variable time delay which exists in mobile radio systems. Accordingly the results is the smaller power control error, that is, the smaller average transmitting power of mobile compared with the conventional control schemes. Because interferences to the other mobiles are reduced, the capacity of CDMA can be increased.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.1
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• pp.14-20
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• 1996

This paper presents a self tuning method of a velocity type PID controller for minimum or non-minimum phase systems with time delays. The velocity type PID control structure is determined in the process of minimizing the variance of the auxilliary output, and 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 a design parameter. This method is simple and effective compared with other existing methods[1,2]. Numerical examples are included to illustrate the procedure and to show the performance of the control system.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.7
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• pp.475-483
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• 1988

One of the advantages of the well-known PID controller is that it is a sufficiently flexible controller for many applications. But, when the plant parameters and disturbances are unknown or change with time, it is desirable to make automatic tuning of PID controller in order to achieve an acceptable level of performance of the control system. This paper presents a reformulation of the self-tuning pole-zero placement controller subject to some conditions and restrictions. It has the structure of a digital PID controller and is based on Vogel and Edgar's pole-zero placement design method. Various properties of this self-tuning PID controller are described and illustrated by simulation examples.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.121-124
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• 2001

In industrial actual control system, PID controller has been used with its high delicate control system in position control system. PID controller has simple structure and superior ability in several characteristics. When the response of system is changed by delay time, variable load , disturbances and external environment, control gain of PID controller must be readjusted on the system dynamic characteristics. Therefore, a control ability of PID controller is degraded when th control gain is inappropriately determined. When the response characteristic of system is changed under a condition, control gain of PID controller must be changed adaptively to be a waited response of system. In this paper an adaptive-tuning type PID controller is constructed by self-recurrent Neural Network(SRNN). applying back-propagation(BP) algorithm. Form the result of computer simulation in the proposed controller, its usefulness is verified.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.229-229
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• 2000

Conventional gain-tuning methods such as Ziegler-Nickels methods, have many disadvantages that optimal control ler gain should be tuned manually. In this paper, modified PID controllers which include self-tuning characteristics are proposed. Proposed controllers automatically tune the PID gains in on-1ine using neural networks. A new learning scheme was proposed for improving learning speed in neural networks and satisfying the real time condition. In this paper, using a nonlinear mapping capability of neural networks, we derive a tuning method of PID controller based on a Back propagation(BP)method of multilayered neural networks. Simulated and experimental results show that the proposed method can give the appropriate parameters of PID controller when it is implemented to DC Motor.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.156-160
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• 2018

In the paper, a kind of self-tuning PID control system is designed to keep the honing coolant temperature constant in the process of automobile engine production. The conventional PID control method and the Fuzzy PID control method both are used to design and make the simulation experiment in Matlab. According to the simulation result, the performance of Fuzzy PID control method is obviously better. The Fuzzy PID control system can react faster to get the target temperature and resume normal when external conditions exchanged.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.505-505
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• 2000

Controlling the process by PID controller is widely used in industry by applying Ziegler-Nichols method in analyzing parameter of the controller. However, in fact. it is still necessary to tune parameter in order to obtain the best process response. This paper presents a Self-Tuning PID controller utilizes the personal computer to synthesize and analyze controller parameter as well as tune for appropriate parameter by using Dahlin method and Extrapolation. Experimental results using a Self-Tuning PID controller to control water level and temperature, it is found that the controller being developed is able to control the process very effectively and provides a good response similar to the controller used in the industry.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1251-1258
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• 1999

The water level control of a steam generator in the unclear power plant is an important process. Most of the water level controllers of the actual plant are PID controllers. But they have limitations in appling for tracking the set point and getting rid of disturbances, so there are some defects to apply in the actual ground even though many research works represented the resolutions to solve it. In this paper, it is suggested that the established simple PID controller in low power has the ability to remove disturbances and trace the set-point, and then possesses the real-time self-tuning function according to the variety of moving peculiarity of a plant. This function realized by making use of fuzzy logic. PID parameters are formulated by a variable ${\alpha}$ and made it fluctuate by a fuzzy inference according to level error and level error change. This mechanism makes application of actual plant effective as well as taking advantage of improving the efficiency of water level controller by way of adding the function of self-tuning instead of replacing PID controller. The computer simulation of this scheme shows the improved performance compare to conventional PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.452-456
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• 1988

A PID controller must need not only good servo response but also little operation of a control valve. We suggest a direct pole-placement PID self-tuning algorithm using the structure of derivative-of-output controller and Bezout identity. This algorithm can much reduce the change of output of controller and well follow the desired trajectory.