• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2584-2586
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• 2000

A drum level control is one of the most important control systems in thermal power plant. The control objective of drum level of boiler in thermal power plant is to maintain drum level at constant set-point regardless of disturbance such as main steam flow. The implemented drum level controller is the cascade PI controller. The important factor in drum level controller is the parameters of two PI controllers. The tuning of PI controller parameter is tedious and time-consuming job. In this paper, the relay feedback Ziegler - Nichols tuning method extended to auto-tune cascade PI drum level controller. Finally, the simulation result using boiler model in Power Plant shows the validity of auto-tuned cascade PI controller.

• 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

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.994-997
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• 2003

Simple tuning formulae are derived to design a Pl controller to meet the gain and phase margin specifications. These formulae are suitable for the auto-tuning of a process where the robustness should be guaranteed. The auto-tuned PI controller is examined for the speed regulation of a PM synchronous motor.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.120.2-120
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• 2002

In this paper auto-tuning scheme of weight function in the neural networks has been suggested by immune algorithm for nonlinear process. A number of structures of the neural networks are considered as learning methods for control system. A general view is provided that they are the special cases of either the membership functions or the modification of network structure in the neural networks. On the other hand, since the immune network 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. Also. It can provi..

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.530-535
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• 2011

This paper deals with the precise temperature control of the heater used at a weaving thread or a drawn process. For precise temperature control, we suggest a design method that is auto-tuning IMC-PID controller using an optimization method uDEAS. For this method, we model the roll heater from the measurement data and we automatically tune the low pass filter value of IMC-PID controller that satisfies stability and conrol performance. Finally, we implement the designed controller using DSP kit.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2139-2142
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• 1997

The most important thing in vector control scheme is the knowledge of accurate electrical motor parameters. These parameters can computed by conventional motor test, such as no-load and locked rotor tests. However, the values from these tests are different from actual motor parameters, and the adjustment process of the parameters is time consuming. This paper presents an auto-tuning method for vector control of induction motor. The tuning algorithm is based on the rotor flux behavior of the induction motor for stepwise torque current command. The transient terminal voltage caused by the undesirable variation of the rotor flux is used for tuning the slip gain $K_5$ defined as the inverse of the rotor time constant. The electrical parameters of induction motor can also calculated by this method. The presented method is evaluated through the computer simulations.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.419-427
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• 2018

This paper designs and develops auto-tuning temperature controller with multi-channel, which controller with multi-channel could control a number of control system simultaneously. This controller has multi-channel input and output. And a number of control algorithms run in this controller simultaneously and independently. Firstly we present design method of controller with multi-channel. Secondly we design electrical circuit of sensor input, controller output and power control for temperature control board. And finally we design data protocol for serial communication to monitor control state and present verification of temperature controller with muiti-channel through field experiment.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.345-348
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• 1991

This paper describes a new auto tuning method for the intelligent PID control system. This new method is hosed on the settling time of the process and has been introduced into auto-tuning PID controller using fuzzy logic. The performance of the controller is measured by computer simulation. Simulation shows good results that controller searches well the optimal values of PID parameters in any conditions and the response characteristic of the control system is improved.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.521-523
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• 1999

In this paper, we propose the hybrid fuzzy controller(HFC) and the hybrid auto-tuning algorithm. The proposed HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance such as sensitivity improvement in steady state and robustness in transient state than any other controller. In addition, a hybrid auto-tuning algorithm which consists of genetic algorithm and complex algorithm to automatically generate weighting factor, scaling factors and PID control gains optimizes the output of HFC. As an typical example of non-linear system in control theory an inverted pendulum will be controlled by the suggested HFC and illustrated the performance and applicability of this proposed method by simulation.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.630-632
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• 2009

The parameters of PID controller should be readjusted whenever system character change. In spite of a rapid development of control theory, this work needs much time and effort of expert. In this paper, to resolve this defect, after the sample of parameters in the changeable limits of system character is obtained, these parametrs are used as desired values of back propagation learning algorithm, also neural network auto tuner for PID controller is proposed by determing the optimum structure of neural network. Simulation results demonstrate that auto-tuning proper to system character can work well.