• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.4
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• pp.603-610
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• 1998

The purpose of this paper is to describe how the characteristics of the movement of cars can be modeled with computers. For this, we use Matlab and simulate the characteristics of the cruise-speed at which the car is driven using the Fuzzy PID controller. The model of the car is designed by M-S(Matlab-Simulink) and each parameter of PID is estimated automatically by the Fuzzy controller. The simulation of the car is carried out on straight base tracks, and then this is compared and analyzed with the simple Fuzzy controller and the simple PID controller.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.57-64
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• 1994

This paper proposes a fuzzy tuning PID controller for straight line type inverted pendulum. The conventional PID controller which is used widely in industrial field has fatal drawback on determining control gains for practical system. The proposed controller tunes the gains automatically based on fuzzy urle derived from the experience of expert operator. The results of simulation and experiment show the efficiency of the proposed control method comparing with conventional PID control method in terms of rising time, overshoot, and overall errors.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.518-528
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• 2015

This article presents a closed loop control of DC series motor fed by DC chopper controlled by an PID controller based intelligent control using ANN (Artificial Neural Network). The PID-ANN controller performances are analyzed in both steady state and dynamic operating condition with various set speed and various load torque. Here two different motor parameters are taken for analysis (220V and 110V motor parameters). The static and dynamic performances are taken for comparison with conventional PID controller and existing work. The steady state stability analysis of the system also made using the transfer function model. The equation model is also done to analysis the performances by set speed change and load torque change. The proposed controller have better control over the conventional PID controller and the reported existing work. This system is initially simulated using MATLAB / Simulink and then experimental setup done using P89V51RD2BN microcontroller.

• Journal of Power Electronics
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• v.16 no.2
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• pp.564-571
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• 2016

This study proposes an adaptive neuro-fuzzy inference system (ANFIS)-based rotor position controller for brushless direct current (BLDC) motors to improve the control performance of the drive under transient and steady-state conditions. The dynamic response of a BLDC motor to the proposed ANFIS controller is considered as standard reference input. The effectiveness of the proposed controller is compared with that of the proportional integral derivative (PID) controller and fuzzy PID controller. The proposed controller solves the problem of nonlinearities and uncertainties caused by the reference input changes of BLDC motors and guarantees a fast and accurate dynamic response with an outstanding steady-state performance. Furthermore, the ANFIS controller provides low torque ripples and high starting torque. The detailed study includes a MATLAB-based simulation and an experimental prototype to illustrate the feasibility of the proposed topology.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.4
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• pp.257-264
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• 2015

For the tracking of the way-points of hovering AUV (HAUV), we suggest a simple PID controller. The way-points are designed to approach to a virtual underwater structure and the heading angles at each way-point are set to look at the structure in the face. The proposed controller consists of a vertical controller to maintain the depth and pitch angle, and a horizontal controller to move to the desired position as well as to adjust the heading angle of the HAUV. In the simulation using Matlab/Simulink, the HAUV with the proposed PID controller is shown to track all the way-points within 1 m range while maintaining proper heading angle at each way-point.

• Journal of Communications and Networks
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• v.6 no.2
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• pp.133-146
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• 2004

Recently, many active queue management (AQM) algorithms have been proposed to address the performance degradation. of end-to-end congestion control under tail-drop (TD) queue management at Internet routers. However, these AQM algorithms show performance improvement only for limited network environments, and are insensitive to dynamically changing network situations. In this paper, we propose an adaptive queue management algorithm, called PID-controller, that uses proportional-integral-derivative (PID) feedback control to remedy these weak-Dalles of existing AQM proposals. The PID-controller is able to detect and control congestion adaptively and proactively to dynamically changing network environments using incipient as well as current congestion indications. A simulation study over a wide range of IP traffic conditions shows that PID-controller outperforms other AQM algorithms such as Random Early Detection (RED) [3] and Proportional-Integral (PI) controller [9] in terms of queue length dynamics, packet loss rates, and link utilization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.380-385
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• 2001

In this paper, in order to get rid of danger trapped Local minimum point, disadvantage of General Back-propagation and simultaneously obtain fast teaming-speed. We propose PID Back-Propagation with Momentum Term(PID-BPMT) and Design PID Controller by Neural Network with Momentum term. Consider to apply for that Controller in position control system by driven D.C servo motor. its useful performance is verified by computer simulation

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.119-121
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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 simple PID controller tuning method for integrating processes with time delay to meet a sensitive function $M_s$. With the proposed PID tuning method, we can obtain stable integrating processes using PD controller in inner feedback loop and a loop transfer function with desired stable specification. This guarantees both robustness and performance. Simulation examples are given to show the good performance of the proposed tuning method to other methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.395-398
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• 2001

In this paper, we consider to apply of 2-DOF (Degree of Freedom) PID controller at D.C servo motor system. Many control system use I-PD, PID control system but the position control system have difficulty in controling variable load and changing parameter. We propose neural network 2-DOF PID control system haying feature for removal disturbances and tracking function in the target value point. Experiment result for 2-DOF PID controller with neural network are illustrated.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1021-1024
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• 1997

This paper has presented a method for self-tuning tile PID controller using a BP method of multilayered NNs. The proposed controller employ input signal as a learning signal of PID control. The proposed controller is applied to load-frequency control of power system and it is investigated a dynamic characteristic. The simulation results shows that proposed NN STPID controller has the good dynamics responses against load disturbances.