• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.337-339
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• 1992

This paper deals with the tuning method of PID controls for process controls. It introduces the normalized process gain and the normalized process dead-time for processes based on Ziegler-Nichols tuning methods. In the case of PID auto-tuning, the first, this method applies Ziegler-Nichols tuning method and introduces the set-point weighting for reducing overshoot in the large normalized process gain or small normalized process dead-time, the second, this method is modified and includes the set-point weighting in the small normalized process gain or large normalized process dead-time. In the case of PI auto-tuning, this method is modified for reducing overshoot. This paper obtains empirical data with Ziegler-Nichols methods for refined Ziegler-Nichols tuning methods.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.85.2-85
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• 2001

In this paper, we propose a modified Ziegler-Nichols PID controller using the fuzzy logic system. The proposed method is to parameterize a Ziegler-Nichols formula with a single parameter, and use the fuzzy logic system for automatic tuning of a single parameter of the modified Ziegler-Nichols formula. The fuzzy logic system has simple nine control rules. In order to verify the effectiveness of the proposed method, we simulated with the servo system. Simulation results demonstrate that better control performance can be achieved when compared with that of the Ziegler-Nichols PID controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.43-46
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• 1998

This paper presents a new parameter tuning method for PID controller. The Ziegler-Nichols Parameter tuning has been widely known as a fairly heuristic method to good determine setting of PID controllers, for a wide range of common industrial processes It has a excessive overshoot in the set point response, set point weighting can reduced the overshoot to specified values. It will also be shown that set point weighting is superior to the conventional solution of reducing large overshoot by other method. In this paper, we will modified the Ziegler-Nichols tuning formula by fuzzy set. These method will give appreciable improvement in the performance of PID controllers.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.8
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• pp.774-781
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• 1991

This paper proposes an auto-tuning method of a discrete -PIC controllers which is based on the Ziegler and Nichols's PID Tuning Rule. This tunign rule is derived using the Pade's first order approximation and it prevents the performance degradation caused by the time-delay effect of zero order holder when the Ziegler-Nichols tuning rule is applied to a discrete PID controller. A simple and practical auto-tuning method is proposed through combining this discrete tuning rule with the relay control. The auto-tuning scheme is implemented on a microprocessor based system and is applied to a position control system to show the effectiveness of the discrete tuning rule.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.5
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• pp.475-481
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• 2009

Real-coded genetic algorithm(RCGA) has better performances than conventional genetic algorithm about dealing with a large domain, the precision and the constrain problem. Also the RCGA has advantage of operation time because it doesn't have to following about decoding operation. In this paper the ranges of PID gains are limited based on Ziegler-Nichols method to consider a long operation time problem that is the main problem of genetic algorithm. Result shows proposed method represents better performance without ignored about result of ZN tuning method and reduces the calculation time.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.775-777
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• 1998

The Ziegler-Nichols parameter tuning has been widely known as a fairly heuristic method to good determine setting of PID controllers, for a wide range of common industrial processes. We extract process knowledge required for rule base controller through tuning experiment and simulation study, such as set point weighting and normalised gain and dead time of process. In this paper, we presents a rule base PID controller by extracted process knowledge and the modified Ziegler-Nichols tuning. Computer simulation are provided demonstrate the feasibility of this approach.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.988-991
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• 2003

In this paper, we try to develop the controller which uses the block diagrams of SIMTool and internal functions CEMTool for planning the global driving controller for high efficiency AGV. We acquire the control efficiency by controlling the motor used each part of AGV driving controller. The block diagram structures provided with SIMTool is easily designed by the controller, and the monitoring and analysis of the results is researched by simulation. We expect to control AGV. robot and various plant using Ziegler-Nichols auto-tuning method and external I/O board

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.195-201
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• 2020

This paper implemented quadcopter-type drone system and proposed the heuristic method for obtaining the optimum gain coefficients in order to minimize the settling time. Control system for quadcopter posture stabilization reads the posture data from accelerator and gyro sensor, revises the original posture data using Mahony filter, and drives 4 DC motors using PID controller. The first step of the proposed method is to obtain the gain coefficients using the Ziegler-Nichols method, and then determine the optimum gain coefficients using the heuristic method at the next 3 steps. The experimental result shows that the maximum overshoot decreases from 44.3 to 29.8 degrees and the settling time decreases from 2.6 to 1.7 seconds compared to the Ziegler-Nichols method. Therefore, we proved that the proposed method works well in quadcopter flight system with high motor noise while reducing trial and error to obtain the optimal PID gain coefficients.

• Journal of the Korean Vacuum Society
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• v.5 no.4
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• pp.284-291
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• 1996

We have implemented a fast pressure control system for the transport chamber of a high vacuum cluster tool for advance semiconductor fabrication and evaluated its performance. To overcome the typically slow response of mass flow controllers, the modified experimental method is used very effectively to optimize the pressure control procedure. We successfully obtained quite fast pressure control by adjusting the starting time and eht tuning constants by the Ziegler-Nichols method. In the transport pressure $10\times 10^{-5}$ torr, actual pressure control starts from 4 sec after an initial gas load of 2.1 sccm. As a result, optimum conditions for the tuning constants are the rise rate of 0.02 torr/sec, the lag time of 0.15 sec, and the sampling period of 0.5 sec. Then the settling time is about 9 sec within about $\pm$0.5% for the referenced value. This settling time is enhanced above 75 percents in comparison with conventional experimental method. To account for the experimental effects observed, a theoretical model was developed. This experimental result has a tendency to fit with the theoretical result of $\omega$=-1.0.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.2
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• pp.219-225
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• 2002

Parameter tuning methods by Ziegler-Nichols for PID controllers are generally classified into Z-N(1) and Z-N(2). The purpose of this paper is to describe what relations exist between the methods of Z-N(1) and Z-N(2), or how Z-N(1) can be originated from Z-N(2) by analyzing one loop control system composing of P or PI controller and time delay process. In this paper, for the first step to seek mutual relations, the simple formulas of Z-N(2) are transformed into those composing of the same parameters as Z-N(1) which is derived from the analysis of frequency characteristics. Then, the approximation of the actual ultimate frequency is proposed as important premise in the translation between Z-N(1) and (2). Such equalization and approximation brings a simple approximated formula which can explain how Z-N(1) is originated from the Z-N(2) in the form of formula.