• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.3 no.1
• /
• pp.79-83
• /
• 2004

This study was how to control the mass flow controller in gas supplying system. The flow controller consists of piezoelectric material and sensor with heating wire. It is difficult to obtain accurate model, because MFC was composed of many parts, and the relationship between input and output of controller is nonlinear. The model for control was obtained by time constant and DC gain Based on this model, PID controller was applied to flow controller using DSP board. Also, the results were compared to controller using system identification.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2001.06a
• /
• pp.121-124
• /
• 2001

In industrial actual control system, PID controller has been used with its high delicate control system in position control system. PID controller has simple structure and superior ability in several characteristics. When the response of system is changed by delay time, variable load , disturbances and external environment, control gain of PID controller must be readjusted on the system dynamic characteristics. Therefore, a control ability of PID controller is degraded when th control gain is inappropriately determined. When the response characteristic of system is changed under a condition, control gain of PID controller must be changed adaptively to be a waited response of system. In this paper an adaptive-tuning type PID controller is constructed by self-recurrent Neural Network(SRNN). applying back-propagation(BP) algorithm. Form the result of computer simulation in the proposed controller, its usefulness is verified.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2002.05a
• /
• pp.310-313
• /
• 2002

In industrial actual control system, PID controller has been used with its high delicate control system in position control system. PID controller has simple structure and superior ability in several characteristics. When the response of system is changed by delay time, variable load , disturbances and external environment, control gain of PID controller must be readjusted on the system dynamic characteristics. Therefore, a control ability of PID controller is degraded when the control gain is inappropriately determined. When the response characteristic of system is changed under a condition, control gain of PID controller must be changed adaptively to be a waited response of system. In this paper an PIDA controller is constructed by Two-Layers Neural Network applying back-propagation(BP) algorithm. Form the result of compute. simulation in the proposed controller, its usefulness is verified.

• Proceedings of the KIPE Conference
• /
• 2014.07a
• /
• pp.556-557
• /
• 2014

This paper presents an artificial intelligence - Deep Belief Network (DBN) gain-scheduling adaptive PI controller scheme for dual active bridge (DAB) converter. The PI gains are allowed to vary within a predetermined range and therefore eliminate the problems faced by the conventional PI controller. The performance of the proposed controller is simulated and compared with the conventional fixed PI controller under various conditions. The experimental prototype of the DAB converter is implemented using a digital signal processor of TMS320F28335 manufactured by Texas Instrument to examine and to evaluate the performance criteria of the proposed controller. Simulation and experimental results show improvements in transient as well as steady state responses of the proposed controller over the conventional fixed PI controller.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.1
• /
• pp.32-39
• /
• 1997

One of the most important performance criteria in tuning the gain of position loop controller for CNC machining center is the contour error. In this papre we analyze contour error in the linear and circular interpolations for the axis-matched and mismatched cases. To have small contour errors, it is necessary to set the P gain for each axis to be same. And the D gain should be much smaller than the P gain. Baded on the analysis in the frequency domain, we propose a gain tuning method for the P and PD controllers. We show that the PD controller is better than the P controller. The effectiveness of this method is demonstrated by experiments.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1652_1653
• /
• 2009

본 논문에서는 passivity based controller에 high gain observer를 접목시킨 유압 모터의 위치 제어기를 제시 한다. 본 논문에서는 5차 비선형 동역학 모델을 사용 하였다. Passivity based controller는 유압 모터의 높은 위치 추정능력을 구현하지만 그것을 위해서는 유압 모터의 상태 및 부하의 정보를 알아야 한다. 상태 및 부하의 정보를 추정 하기 위하여 high gain observer를 제안하였다. High gain observer을 사용함으로서 유압 모터와 부하의 동역학의 비선형성을 줄여 상태 및 부하를 효과적으로 추정 하였다. 유압 모터의 위치 제어 성능 및 부하의 관측 능력 평가를 위하여 Matlab/Simulink를 이용하여 모의 실험을 구현 하였다.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.15 no.5 s.98
• /
• pp.578-585
• /
• 2005

In this paper, we present a schematic method estimating the tracking vibration quantity occurring in the track-following system of an optical recording device. A tracking loop gain adjustment algorithm is introduced to estimate accurately the tracking vibration quantity in spite of the uncertainties of the tracking actuator, Accordingly, the tracking vibration quantity can be estimated from the tracking error, the controller output, the nominal actuator model, and a compensated gain. An optimal tracking controller can be designed from a minimum tracking open-loop gain calculated by the estimated tracking vibration quantity The proposed vibration quantity estimation and controller design method are applied to the track-following system of an optical recording device and are evaluated through the experimental result.

• International Journal of Precision Engineering and Manufacturing
• /
• v.9 no.4
• /
• pp.39-44
• /
• 2008

In this paper, through the study of discrete implementation of time delay control (TDC) and PID control algorithm, a new systematic gain selection method for PID controller is proposed. An important advantage of this method is that it may be applied to real systems with very simple and systematic procedure. The proposed method is derived for SISO systems and then extended to MIMO system. Through simulation for the second order non-linear plant and experiment on 2-DOF robot, the effectiveness of the proposed method is confirmed. The proposed method could solve the problem of difficulty in gain tuning of existing PID controller.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.22 no.1
• /
• pp.1-6
• /
• 2014

In this paper, controller propose to prevent compressor surge and improve the transient response of the fuel flow control system of turbojet engine. Turbojet engine controller is designed by applying Artificial Neural Network PID control algorithm and make an inference by applying Levenberg-Marquartdt Error Back Propagation Algorithm. Artificial Neural Network inference results are used as the fuel flow control inputs to prevent compressor surge and flame-out for turbojet engine for UAV. High Gain Observer is used to estimate to compressor rotation speed of turbojet engine. Using MATLAB to perform computer simulations verified the performance of the proposed controller. Response characteristics pursuant to the gain were analyzed by simulation.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.51 no.4
• /
• pp.195-202
• /
• 2002

The high performance position controller named 'Unified PID Position Controller'is presented in part 1 of this paper. In part 2, we provide smart gain adjustment methods including the freedom utilizations for rare sensitivity toward the system parameter variation and for increasing the stiffness of the system. Owing to the provided gain tuning strategy, the overall system characteristics can be stabilized without over-shoot phenomena when the system parameter is changed in the rate of from 0.5 to 2∼4. Moreover, for the actual feasibility to the industrial fields, a simple butt effective anti-windup strategy prohibiting the integral component of the PID position controller from saturation is presented too. All of the presented algorithms are verified through the experiment works with commercial linear motor.