• Journal of Advanced Marine Engineering and Technology
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• v.30 no.7
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• pp.791-799
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• 2006

The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.63-70
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• 1999

This paper is proposed a new method to deal with the optimized auto-tuning for the Pill controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nichols method. So we can find the parameters of Pill controller so as to minimize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. Finally, after studying the parameters of Pill controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of Pill controller is found by Neural-Network Program.rogram.

• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1074-1085
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• 2004

There are many intermediate web guides in cold rolling mills process such as CRM (cold rolling mill), CGL (continuous galvanizing line), EGL (electrical galvanizing line) and so on. The main functions of the web guides are to adjust the center line of the web (strip) to the center line of the steel process. So they are called CPC (center position control). Rapid process speed cause large deviation between the center position of the strip and the process line. Too much deviation is not desirable. So the difference between the center position of the strip and the process line should be compensated. In general, the center position control of the web is obtained by the hydraulic driver and electrical controller. In this paper, we propose modelling and several controller designs for web-guide systems. We model the web and guide by using geometrical relations of the guide ignored the mass and stiffness of the web. To control the systems, we propose PID controllers with their gains tuned by the Ziegler-Nichols method, the H$\_$$\infty$/ controller model-matching method, and the coefficient diagram method (CDM). CDM is modified for high order systems. The results are verified by computer simulations.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.94-98
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• 1999

Optical scanning systems use glavanometers to point the laser beam to the desired position on the workpiece. The angular speed of a galvanometer is typically controlled using Proportional+Integral+Derivative(PID) control algorithms. However, natural variations in the dynamics of different galvanometers due to manufacturing, aging, and environmental factors(i.e., process uncertainty) impose a hard limit on the bandwidth of the galvanometer control system. In general, the control bandwidth translates directly into efficiency of the system response. Since the optical scanning system must have rapid response, the higher control bandwidth is required. Auto-tuning PID algorithms have been accepted in this area since they could overcome some of the problems related to process uncertainty. However, when the galvanometer is attached to a larger mechanical system, the combined dynamics often exhibit resonances. It is well understood that PId algorithms may not have the capacity to increase the control bandwidth in the face of such resonances. This paper compares the achieable performance and robustness of a galvanometer control system using a PID controller tuned by the Ziegler-Nichols method and a controller designed by the Quantitative Feedback Theory(QFT) method. The results clearly indicate that-in contrast to PID designs-QFT can deliver a single, fixed controller which will supply high bandwidth design even when the dynamics is uncertain and includes mechanical resonances.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.278-280
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• 1999

This paper proposes controlling of temperature in an oven by using 4 bits Integral - Cycle Binary Rate Modulation (IBRM) method and ac line with frequency 50 Hz. Microcontroller MCS-51 controls IBRM according to Proportional Integral controller (PI) function. Discrete signals are used in the system modeled by using Ziegler Nichols principle for analyzing the stability before designing the system. This procedure makes it easy to investigate system response. The system is implemented by 4 bits digital circuit which gives 320 patterns of ac signal fur controlling the generation of energy for 3,000 watts thermal coil every 20 ms of each cycle. We divide scan time (Ts$\sub$n/) in to 20 intervals, 1 ms interval is selected to generate 16 patterns IBRM. Because of this method gives the ripple lower than 2% it generates less noise fur system. Moreover, we can consider whole system from the time model of control procedure and IBRM algorithm at 40-200$^{\circ}C$ with ${\pm}$ 1$^{\circ}C$ error in the 1 cubic meter oven.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.288-291
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• 1999

The PID (Proportional-Integral-Derivative) controller is widely used in the industries for more than fifty years with the well known Ziegler-Nichols tuning method and others varieties. However, most of the PID controller being used in the real practice still require trial and error adjustment for each process after the tuning method is done, which is consuming of time and needs the operator experiences to obtain the best results for the controller parameter. In order to reduce the inconvenience in the controller tuning, this paper presents a design of an automatic PID controller parameter analyzer being used as a support instrument in the industrial process control. This analyzer is designed based on the tuning formula of Dahlin to synthesize the PID controller parameter. Using this analyzer, the time to be spent in the trial and error procedures and its complexity can be neglected. Experimental results using PID controller parameter synthesized from this analyzer to the liquid level control plant model and the fluid flow control plant model show that the responses of the controlled systems can be efficiently controlled without any difficulty in mathemathical computation.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.43 no.3
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• pp.1-10
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• 2011

Proportional.Integral.Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. However PID controller is poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This research comes up with a soft computing approach involving Genetic Algorithm, Evolutionary Programming, and Particle Swarm Optimization and Ant colony optimization. The proposed algorithm is used to tune the PID parameters and its performance has been compared with the conventional methods like Ziegler Nichols and Lambda method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. This research addresses comparison of tuning of the PID controller using soft computing techniques on Machine Direction of basics weight control in pulp and paper industry. Compared to other conventional PID tuning methods, the result shows that better performance can be achieved with the soft computing based tuning method. The ability of the designed controller, in terms of tracking set point, is also compared and simulation results are shown.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.827-836
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• 2001

The PID controller has been widely applied to the most control systems because of its simple structure and east designing. One of the important points to design the PID control system is to tune the approximate control parameters for the given target system. To find the PID parameters using Ziegler Nichols(ZN) method needs a lot of experience and experiments to ensure the optimal performance. In this paper, CMIA(Cell Mediated Immune Algorithm) controller is proposed to drive the autonomous guided vehicle (AGV) more effectively. The proposed controller is based on specific immune responses of the biological immune system which is the cell mediated immunity. To verify the performance of the proposed CMIA controller, some experiments for the control of steering and speed of that AGV are performed. The tracking error of the AGV is mainly investigated for this purpose. As a result, the capability of realization and reliableness are proved by comparing the response characteristics of the proposed CMIA controllers with those of the conventional PID and NNPID(Neural Network PID) controller.

• Journal of Biosystems Engineering
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• v.34 no.5
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• pp.305-314
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• 2009

The purpose of this paper was to design an effective control system of 1-axis exciter for a seat vibration test of agricultural tractors using MATLAB simulation. The developed simulation model was composed with a hydraulic pump, a hydraulic servo valve, a hydraulic cylinder and load system. Also it was verified by comparing the simulation results with experimental results of actual control system in order to optimize the control performance. And in order to improve its control performance, the designed PID controller in this research was tuned using Ziegler-Nichols 2nd law and zero's moving method of PID controller's transfer function. As the result of these research, the developed position control system was able to control the system's position accurately within 5% errors.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.95-103
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• 2001

The purpose of Introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. The efficiency of a combined power plant with the gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a combined 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul, Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controllers.