• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.246-254
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• 2002

In this paper auto-tuning scheme of PID controller based on the reference model has been studied for a Process control system by immune algorithm. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. Also, a number of approaches have been proposed to implement mixed control structures that combine a PID controller with fuzzy logic. However, in the actual plant, they are manually tuned through a trial and error procedure, and the derivative action is switched off. Therefore, it is difficult to tune. Since the immune system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (Parallel Distributed Processing) network to complete patterns against the environmental situation. Simulation results reveal that reference model basd tuning by immune network suggested in this paper is an effective approach to search for optimal or near optimal process control.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.724-728
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• 1987

Recently, two degrees of freedom PID control systems have attracted attention, because of their better process control quality for both set point variable tracking and disturbance resistivity than that of conventional PID control systems. This paper describes a new auto-tuning method for the two degrees of freedom PID control system based on a newly developed model matching method in the frequency domain. This new method has been introduced into a two degrees of freedom PID auto-tuning controller, named AdTune TOSDIC-21D8. The superior features of the controller and the results of field tests Are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.974-981
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• 2009

In this paper, a method of auto-tuning of PID (Proportional-Integral-Derivative) and PIDA (Proportional-Integral-Derivative-Acceleration) controllers is proposed that can be applied to a time-delayed second order model. The proposed identification method is based on step responses, but it can be easily automated rising digital controller unlike the existing graphical identification methods. We provide a ways to yield parameter identifications which is independent to initial values of the plants. The tuning rule is based on the pole-placement strategy and is formulated so that it can be implemented using a digital controller with ease.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.504-506
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• 1999

In this paper, we propose a method which control parametric uncertainty systems using PID controller by fuzzy auto tuning. We get the error and the error change rate of plant output correspond to the initial value of parameter using the Ziegler-Nickols tuning and determine the new proportional gain$(K_p)$ and the integral time $(T_i)$ from fuzzy tuner by the error and error change rate of plant output as a membership function of fuzzy theory. The Fuzzy Auto-tuning algorithm for PID controller operate to adapt variable parameter of plant in parametric uncertainty systems. It is shown this method considerably improve the transient response at computer simulation.

• Journal of the Korea Convergence Society
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• v.4 no.2
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• pp.43-50
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• 2013

Sliding mode control(SMC) are carried out in this literature. And to make the controllers perform better, fuzzy logic was chosen,it makes PID controller auto-tuning parameters and reduced the chattering problem of sliding mode control. Since SMC take error and derivative of error as inputs, after comparison some results are obtained.PID controller response faster yet sliding mode control is much steadier. However certain problems cannot be ignored that the chattering phenomenal cannot be reduced entirely and this motion may hurt the machine; this project only considered a simple system, there is no guarantee PID can work as well as in this case for a much more complex system. MATLAB simulink was the main approach to obtain the performance of the two controllers: to observe the control output of the two controllers, electric circuit and special controllers are designed and tested in MATLAB.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1008-1011
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• 1996

Most control systems of power plants are using classical PID controllers for their process control. In order to get the desired control performances, the correct tuning of PID controllers is very important. Sometimes, it is necessary to retune PID controllers after the change of system operating condition and system design change, etc. Commercial auto-tuning controllers such as relay feedback controller can be used for this purpose. However, using these controllers to the safety-critical systems of nuclear power plants may be cause of unsafe operation, because they are using test signals for tuning. A new system identification auto-tuning method without using test signal has been developed in this paper. This method uses process input/output signals for system identification of unknown control process. From the model information of control process which was obtained from system identification approach, the optimal PID parameters can be calculated. The method can be used in the safety-critical systems because it is not using test signals during system modeling process.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.68-71
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• 1990

In this paper, it is introduced about Auto-Tuning Method which applied to Expert Controller. This method constructs heuristic knowledge of the tuning experiment in order to realize relay tuning theory of Astrom &. Hagglund. This method applies to various Plant and showes utility which is used for Controller design of PID group. Result of simulation showed superiority for speed reponse and robustness of all Plant.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.501-503
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• 1999

In this paper, the design method of a hybrid fuzzy controller with an optimal auto-tuning method is proposed. The conventional PID controller becomes so sensitive to the control environments and the change of parameters that the efficiency of its utility for the complex and nonlinear plant has been questioned in transient state. In this paper, first, a hybrid fuzzy logic controller(HFLC) is proposed. The control input of the system in the HFLC is a convex combination by a fuzzy variable of the FLC's output in transient state and the PID's output in steady state. Second, a powerful auto-tuning algorithm is presented to automatically improve the Performance of controller, utilizing the improved complex method and the genetic algorithm. The algorithm estimates automatically the optimal values of scaling factors and PID coefficients. Controllers are applied to the plants with time-delay and the DC servo motor Computer simulations are conducted at the step input and the system performances are evaluated in the ITAE.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.178-187
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• 2007

One important issue in power systems is dynamic instability due to loosing balance relation between electrical generation and a varying load demand that justifies the necessity of stabilization. Moreover, Power System Stabilizer (PSS) must have capability of producing appropriate stabilizing signals over a wide range of operating conditions and disturbances. To overcome these drawbacks, this paper proposes a new method for robust design of PSS by using an auto-tuning fuzzy control in combination with Real-Coded Genetic Algorithm (RCGA). This method includes two fuzzy controllers; internal fuzzy controller and supervisor fuzzy controller. The supervisor controller tunes the internal one by on-line applying of nonlinear scaling factors to inputs and outputs. The RCGA-based method is used for off-line training of this supervisor controller. The proposed PSS is tested in three operational conditions; nominal load, heavy load, and in the case of fault occurrence in transmission line. The simulation results are provided to compare the proposed PSS with conventional fuzzy PSS and conventional PSS. By evaluating the simulation results, it is shown that the performance and robustness of proposed PSS in different operating conditions is more acceptable

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.129-130
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• 2007