• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.2010-2016
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• 2007

PID control is windely used to control stable processes, However, its application to integrating processes is less common. In this paper, we proposed a stable PID controller tuning method for integrating processes with time delay using model reduction method. For proposed model reduction method, it disconnect an integrating factor from integrating processes and reduces separate process using reduction method. and it connect an integrating factor to reduced model. We can obtain stable integrating processes using P controller in inner feedback loop and PID tuning is then used to cancel the pole of the feedback loop. This guarantees both robustness and performance. Simulation examples are given to show the good performance of the proposed tuning method comparing with other methods.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2651-2654
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• 2000

In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a self tuning fuzzy PID controller whose input output scaling factors were tuned automatically. At first stage, the tuning parameters of fuzzy controller were determined by Ziegler-Nichols tuning method and then they were adjusted as the delay time and process environment were changed. Proposed controller was simple in its structrue and computational burden was small so that on line adaptation was easy to apply to. The result of computer simulation and practical experiment showed the proposed controller's excellent performance

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.964-967
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• 1993

This paper presents an auto tuning method of fuzzy inference using Genetic Algorithm. The determination of membership functions by human experts is a difficult problem. Therefore, some auto-tuning methods have been proposed to reduce the time-consuming operations. However, the convergence of the tuning by the previous methods depends on the initial conditions of the fuzzy model. So, we proposes an auto tuning method for the fuzzy neural network by Genetic Algorithm (ATF system). This paper shows effectiveness of the ATF system by simulations.

• Journal of KIISE:Databases
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• v.31 no.4
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• pp.373-383
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• 2004

There have been an emerging interests in the importance of database tuning techniques under modem database environments in which very large-scale data should be managed. In Particular. database performance parameters should be tuned to reflect system loads appropriately. This paper presents two parameter tuning strategies, namely throughput-based and response-time-based, which tune each performance parameter accordingly. The proposed techniques are applied to two commercial database systems in the TPC-W benchmark to see the effectiveness of those methods. The results show that they can help improve system performance considerably.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.1
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• pp.22-30
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• 2001

This paper describes a neural network based fuzzy PID control scheme. The PID controller is being widely used in industrial applications. However, it is difficult to determine the appropriated PID gains in nonlinear systems and systems with long time delay and so on. In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a neural network based self tuning fuzzy PID controller of which output gains were adjusted automatically. The tuning parameters of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods. Then they were adjusted by using proposed neural network learning algorithm. Proposed controller was simple in structure and computational burden was small so that on-line adaptation was easy to apply to. The experiment on the magnetic levitation system, which is known to be heavily nonlinear, showed the proposed controller's excellent performance.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.8-17
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• 2002

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.1-6
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• 2007

This paper presents a new experimental Servo-Parameter tuning technique for a 6-axes articulated robot manipulator, especially considering robot's dynamics. First of all, investigation for proportional gain of velocity control loop by using a Dynamic Signal Analyzer(DSA) is performed. Using the FUNCTION characteristic of DSA based on the Bode plot, the Bode plot of open loop transfer function can be obtained. In turn, the integral gain of a servo controller can be found out by using the integration time constant extracted from the Bode plot of open loop transfer function. In the meanwhile, the positional gain of the servo controller can be obtained by using the Bode plot of the closed loop transfer function. Using the experimental gain tuning technique proposed in this paper, the testing linear motion of DR6-II robot has been shown to be more accurate rather than the motion with a conventional(empirical) gain tuning technique in Doosan Mecatec Co., Ltd., by improving the dynamic response of the robot as well as synchronizing each joint velocity according to the positional command of an end-effector.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.12
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• pp.43-52
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• 1999

We propose a new method for tuning of center wavelength in photorefractive filter using $LiNbO_3$ crystal doped with 0.015Wt.% Fe. through the filter bandwidth property analysis using the geometrical method, a new wavelength selectivity theory was presented. In this scheme, the tuning of the center wavelength can be achieved by the real time incident angle control of the received heam, which was gotten by the spatial light modulator. So, tuning time depend on the response time of the SLM and results in the high speed turing. Because the use of thermally fixed grating in our filter, it has uniform diffraction property to the all filtering wavelength. Designed tunable filter has 4nm bandwidth and composed of the three channel with 10nm space. From the optical experiment, we get the 4.5nm, 4.25nm, 4nm bandwidth and 1530.5nm, 1540.5nm, 1549.5nm center wavelength respectively.