• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.807-815
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• 2004

This paper describes the design principle of a fuzzy PID controller with fixed parameters, proposes the simulified form of a fuzzy PID controller to increase the computational efficiency and analyzes stability of a proposed fuzzy PID controller. After a detailed stability analysis using ‘small gain theorem’, a simple and practical sufficient condition for the BIBO stability of the overall feedback control system is derived. The derived stability condition offers a calculation method to obtain parameters of a fuzzy PID controller from parameters of a stable PID controller. Finally several computer simulations are executed to confirm the effectiveness of the fuzzy PID controller with fixed parameters.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.888-892
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• 2002

In this paper, parallel type fuzzy controller is designed by using a hybrid connected type fuzzy-PID controller and a model reference fuzzy controller. The first controller that consists a fuzzy-PI and a fuzzy-PD making a hybrid type fuzzy-PID controller plays a role as firstly reaching stable responses and secondly overcoming disturbance in plants. The second controller, model reference fuzzy controller, plays a role as reaching faster responses than other controllers. We have confirmed that we get rapid and stable responses and the controller overcomes disturbance in a short time when there happens disturbance by using parallel type fuzzy controller applying to DC motor in this paper.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.1
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• pp.63-66
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• 1995

PID controller is being used in many servo control system. However, when a control system has variable load, it is difficult to guarantee the accurate control of the system. In the way of solving this problem, in this paper, a auto-tuning method of PID controller parameter using fuzzy rule in variable load is presented. The parameter of PID controller are decided by fuzzy rule according to load variation. The accurate control function of fuzzy auto-tuning is demonstrated by simulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.823-829
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• 2006

In this paper presents approaches to the design of a hybrid fuzzy logic proportional plus conventional integral- derivative(fuzzy P+ID) controller in an incremental form. This controller is constructed by using an incremental fuzzy logic controller in place of the proportional term in a conventional PID controller. The PID type controller has been widely used in industrial application due to its simply control structure, easy of design, and inexpensive cost. However, control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. This paper presents a hybrid fuzzy logic proportional plus conventional integral derivative controller In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the Fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the Fuzzy P+ID controller without modifying the original controller parameters. Finally, the proposed hybrid Fuzzy P+ID controller is applied to BLDC motor drive. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.48-55
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• 2008

In this paper, we propose a hybrid fuzzy controller for high performance. Hybrid fuzzy controller are combined Fuzzy and PID controller. In tuning the controller, the parameters of PID and the factors fuzzy controllers were obtained from the model identification and by using genetic algorithms, respectively. Simulation examples demonstrated a better performance of the proposed controller than conventional ones.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.830-836
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• 2006

In this paper described an auto tuning neuro-fuzzy PID controller based neural network. The PID type controller has been widely used in industrial application due to its simply control structure, easy of design, and inexpensive cost. However, control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. In this paper will design to take advantage of neural network fuzzy theory and pid controller auto toning technique. The value of initial scaling factors of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods and then they were adjusted by using neural network control techniques. This controller simple structure and computational complexity are less, and also application is easy and performance is excellent in system that is strong and has nonlinearity to system dynamic behaviour change or disturbance. Finally, the proposed auto tuning neuro-fuzzy controller is applied to magnetic levitation. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.69-77
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• 1999

This paper describes the design of fuzzy digital PID controller using 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 digital controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional digital 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 SIM 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 the superior to the control performance of the one proposed by D. Misir et al.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2352-2360
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• 2007

Due to the friction characteristics of cylinders and the rail of a passenger car, in the elevator actuated with hydraulic systems, there exist dead zones, which can not be controlled by a PID controller. In this paper, the friction characteristics of a cylinder is examined, which may cause the abrupt increase of the acceleration in the zero-costing speed region. To overcome the drawbacks of a PID controlled hydraulic elevator system, a zooming fuzzy logic controller is designed and finally an improved hybrid fuzzy controller is proposed. The effectiveness of the proposed control scheme are shown by simulation and experimental results, which the proposed fuzzy hybrid control method yields good control performance not only in the zero-crossing speed region but also in the overall control region including steady-state region.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.1
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• pp.55-64
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• 2002

Due to the friction characteristics of cylinders and the rail of a passenger car, in the system actuated with hydraulic systems, there exist dead zones, which can not be controlled by a PID controller. In this paper, the friction characteristics of a cylinder is examined, which may cause the abrupt increase of the acceleration in the zero-crossing speed region. To overcome the drawbacks of a PID controlled hydraulic system, a zooming fuzzy logic controller is designed and finally an improved hybrid controller is Proposed. The proposed controller is composed of the PID controller and the zooming fuzzy controller. The effectiveness of the proposed control scheme is shown by simulation and experimental results, In which the proposed hybrid control method yields good control performance not only in the zero-crossing speed region but also In the overall control region including steady-state region.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.85-90
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• 2003

This paper presents an adaptive PID control scheme for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model is used to estimate the error of control input, and the parameters of PID controller are adapted using the error. The parameters of TSK fuzzy model also adapted to plant. The proposed algorithm allows designing adaptive PID controller which Is adapted to the uncertainty of nonlinear plant and the change of parameters. The usefulness of the proposed algorithm is also certificated by the several simulations.