• 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.

• 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.

• Journal of Biosystems Engineering
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• v.33 no.2
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• pp.115-123
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• 2008

This study was conducted to develop an automatic soil water content control system for greenhouse, which consisted of drip irrigation nozzles, soil water content sensors, an on/off valve, a servo-motor assembly and a control program. The control logic adopted in the system was Ziegler-Nichols algorithm and rising time, time constant and over/undershoot ratio as control variables in the system was selected and determined by various control experiments to maintain small delay time and low overshoot. Based on the experimental results, it was concluded that the control system developed in the study could replace the unreliable conventional greenhouse soil water management.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.36-42
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• 1996

In this paper, we proposed a PID controller, which could control unknown plants using Artificial Neural Network(ANN) for auto-tuning of the PID parameters. In the proposed algorithm, the parameters of the controller were adjusted to reduce the error of the controlled plant. In this process, the sensitivity between input and output of the unknown plant was needed. So, in order to obtain this sensitivity, the ANN's learnig ability was used. Computer simualtions were performed for the regulation problems, and the results were compared with those of Ziegler-Nichols PID controller. As a result, it was shown that the proposed algorithm outperformed Ziegler-Nichols controller in rise time, overshoot, undershoot, and setting time.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.2
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• pp.55-61
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• 2000

In this paper, we proposed a new PID tuning algorithm by the fuzzy set theory to improve the performance of the PID controller. The new tuning algorithm for the PID controller has the initial value of parameter Kc, $\tau$I, $\tau$D by the Ziegler-Nichols formula using the ultimate gain and ultimate period from a relay tuning experiment. We get error and error change of plant output correspond to the initial value and new proportion gain(Kc) and integral time($\tau$I) from fuzzy tunner. This fuzzy tuning algorithm for PID controller considerably reduced overshoot and rise time compare to any other PID controller tuning algorithms. In real parametric uncertainty systems, the PID controller with Fuzzy auto-tuning give appreciable improvement in the performance. The significant properties of this algorithm is shown by simulation In this paper, we proposed a new PID algorithm by the fuzzy set theory to improve the performance of the PID controller.

• Journal of Engineering Education Research
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• v.19 no.2
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• pp.3-7
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• 2016

A flow control system was designed and fabricated to control the flow rate of liquid through the pipe. This control system was composed of hardwares and software, hardwares as controller, gate valve, orifice meter and data aquisition board and software as National instruments Labview program. Control of flow rate was executed by adjusting the pneumatic valve located at the center of pipe line based on the control signal generated by LabView PID control algorithm, which converts analog signal measured by pressure difference of orifice to digital signal to adjust pneumatic valve. For the controller setup Ziegler-Nichols tuning technique was applied and control performances were investigated for not only the disturbance but also the set point changes. Developed system showed good control performances in flow control enough to use as teaching tool of feedback control theory and practice in university, and also as industrial application.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.111-116
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• 2004

In this paper, parameters of a given DC motor system are estimated using the model adjustment technique and the real coded genetic algorithm(RCGA) technique. A number of tuning methods, based on experience and experiment, such as Ziegler-Nichols, Cohen-Coon, IMC, L-ITAE Method have been proposed to obtain parameters for the PID controller. This paper proposes estimating parameters of PID controller using RCGA. The performance of the proposed algorithm is demonstrated through simulations and experiences.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1297-1302
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• 2014

This paper presents modern optimization methods for determining the optimal parameters of proportional-integral-derivative (PID) controller for coupled tank systems. The main objective is to obtain a fast and stable control system for coupled tank systems by tuning of the PID controller using the Particle Swarm Optimization algorithm. The result is compared in terms of system transient characteristics in time domain. The obtained results using the Particle Swarm Optimization algorithm are also compared to conventional PID tuning method like the Ziegler-Nichols tuning method, the Cohen-Coon method and IMC (Internal Model Control). The simulation results have been simulated by MATLAB and show that tuning the PID controller using the Particle Swarm Optimization (PSO) algorithm provides a fast and stable control system with low overshoot, fast rise time and settling time.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.9
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• pp.1065-1071
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• 2012

Wind energy is becoming one of the most preferable alternatives to conventional sources of electric power that rely on fossil fuels. For stable electric power generation, constant rotating speed control of a wind turbine is performed through pitch control and stall control of the turbine blades. Recently, variable pitch control has been implemented in modern wind turbines to harvest more energy at variable wind speeds that are even lower than the rated one. Although wind turbine pitch controllers are currently optimized using a step response via the Ziegler-Nichols auto-tuning process, this approach does not satisfy the requirements of variable pitch control. In this study, the variable pitch controller was optimized by a genetic algorithm using a neural network model that was constructed by the Latin Hypercube sampling method to improve the Ziegler-Nichols auto-tuning process. The optimized solution shows that the root mean square error, rise time, and settle time are respectively improved by more than 7.64%, 15.8%, and 15.3% compared with the corresponding initial solutions obtained by the Ziegler-Nichols auto-tuning process.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.3
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• pp.293-300
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• 2007

The aim of this paper is to design a speed controller of a DC motor by selection of a PID parameters using genetic algorithm. The model of a DC motor is considered as a typical non-oscillatory, second-order system, And this paper compares three kinds of tuning methods of parameter for PID controller. One is the controller design by the genetic algorithm. second is the controller design by the model matching method third is the controller design by Ziegler and Nichols method. It was found that the proposed PID parameters adjustment by the genetic algorithm is better than the Ziegler & Nickels' method. And also found that the results of the method by the genetic algorithm is nearly same as the model matching method which is analytical method. The proposed method could be applied to the higher order system which is not easy to use the model matching method.