• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.991-997
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• 2013

In this paper, we propose a CFWC (CCD and fuzzy PID based width control) scheme to obtain the desired delivery width margin of a vertical rolling mill in hot strip process. A WMS(width measurement system) is composed of two line scan cameras, an edge detection algorithm, a glitch filter, and so on. A dynamic model of the mill is derived from a gauge meter equation in order to design the fuzzy PID controller. The controller is a self-learning structure to select the PID gains from the error and error rate of the width margin. The effectiveness of the proposed CFWC is verified from simulation results under a width disturbance of the entry in the mill. Using a field test, we show that the performance of the width control is improved by the proposed control scheme.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.1
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• pp.136-144
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• 2004

In general a hydraulic system which uses a single rod hydraulic as an actuator is modeled as a nonlinear system and reveals uncertain Parameter characteristics such as the density variation of hydraulic oil and is subject to load variations and severe disturbances during operation. A variable design-parameter fuzzy PID controller is adopted to solve these undesirable internal and external problems and its effectiveness is verified through computer simulations for control performance and real time control possibility.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1577-1586
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• 2017

The Proportional-Integral-Derivative (PID) controller is still the most widespread control strategy in the industry. PID controllers have gained popularity due to their simplicity, better control performance and excellent robustness to uncertainties. This paper presents the optimal tuning of a PID controller for domestic induction heating systems with a series resonant inverter for controlling the induction heating power. The objective is to design a stable and superior control system by tuning the PID controller with a derivative filter (PIDF) through Fuzzy logic. The paper also compares the performance of the Fuzzy PIDF controller with that of a Ziegler-Nichols PID controller and a fine-tuned PID controller with a derivative filter. The system modeling and controllers are simulated in MATLAB/SIMULINK. The results obtained show the effectiveness and superiority of the proposed Fuzzy PID controller with a derivative filter.

• Journal of Electrical Engineering and Technology
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• v.7 no.5
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• pp.724-729
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• 2012

A fuzzy PID controller design method is proposed for precise robust control of DC-DC buck converters. The PID parameters are determined reflecting on the common control engineering knowledge that transient performances can be improved if the P and I gains are big and the D gain is small at the beginning. Different from the previous fuzzy control design methods, the proposed method requires no defuzzification module and the global stability of the proposed fuzzy control system can be guaranteed. The proposed fuzzy PID controller is implemented by using a low-cost 8-bit microcontroller, and simulation and experimental results are given to demonstrate the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1064-1067
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• 1996

This paper describes the design and implementation of an intelligent controller for continuous casting process. The proposed controller adopted a fuzzy control with feedback linearization. The simulation result shows that proposed intelligent controller is superior to the conventional PID controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.120-125
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• 2005

In this paper, We propose the fuzzy controller for the gain tuning of PID controller The proposed controller doesn't use the crisp output error and rule tables though with a fuzzy inference process in forward fuzzifier, New Fuzzy PID Controller assigns relations and ranges of two variables of PID gain parameters. These new gain parameters are calculated by the fuzzy inference with max-min ranges of Kp and Kd. The Ki parameter is computed automatically between Kp and Kd parameter Is calculated by Ziegler-Nickels tuning rules. Finally we experimented the propose controller by the hydraulic servo motor control system. We can obtained desired results through the good control characteristics.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.35-41
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• 2000

This paper describes the design of fuzzy digital PID controller using a simplified indirect inference method. First, the fuzzy digital PID controller is derived from the conventional continuous-time linear digital PID controller,. Then the fuzzification, control-rule base, and defuzzification using SIM in the design of the fuzzy controller are discussed in detail. The resulting controller is a discrete-time fuzzy version of the conventional PID controller, which has the same linear structure, but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIIM is applied the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated that the proposed method provides better control performance than the one proposed by D. Misir et al.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.72-81
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• 2000

In this paper, we design an adaptive neuro-fuzzy inference system(ANFIS) precompensator for load frequency control of 2-area power systems. While proportional integral derivative (PID) controllers are used in power systems, they may have some problems because of high nonlinearities of the power systems. So, a neuro-fuzzy-based precompensation scheme is incorporated with a convectional PID controller to obtain robustness to the nonlinearities. The proposed precompensation technique can be easily implemented by adding a precompensator to an existing PID controller. The applied neruo-fuzzy inference system precompensator uses a hybrid learning algorithm. This algorithm is to use both a gradient descent method to optimize the premise parameters and a least squares method to solve for the consequent parameters. Simulation results show that the proposed control technique is superior to a conventional Ziegler-Nichols PID controller in dynamic responses about load disturbances.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.4
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• pp.87-100
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• 1995

In order to control systems which contain nonlinearities of uncertainties, control strategies must deal with the effects of them. Since most of control methods based on system mathematical models have been mainly developed focused on stability robustness against nonlinearities or uncertainties under the assumption that controlled systems are linear time invariant, they have certain amount of limitations to smartly improve the transient responses of systems disturbed by nonlinearities or uncertainties. In this paper, a nonlinear fuzzy PID control method is suggested which can stably improve the transient responses of systems disturbed by nonlinearities, as well as systems whose mathematical characteristics are not perfectly known. Although the derivation process is based on the design process similar to general fuzzy logic controller, resultant control law has analytical forms with time varying PID gains rather than linguistic forms, so that implementation using common-used versatile microprocessors cna be achieved easily and effectively in real-time control aspect.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.57-62
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• 1998

This paper presents an auto tuning method of PID controller based on the application of fuzzy logic. The proposed method combined the principles of PID control with fuzzy control, which cam considerably improve the performance index of PID controller. Simulation results show that higher performance and accuracy of overall system for desired value is achieved with our manner when compared to widely-used conventional tuning method.