• Title/Summary/Keyword: Self-tuning Control

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The Design Self Compensated PID Controller and The Application of Magnetic Levitation System (신경회로망을 이용한 자기 보상 PID 제어기 설계와 자기부양시스템 적용 실험)

  • Kim, Hee-Sun;Lee, Chang-Goo;Kim, Sung-Joong
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.499-501
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    • 1998
  • In this paper, we present a self-compensating PID controller which consists of a conventional PID controller that controls the linear components and a neural controller that controls the higher order and nonlinear components. This controller is based on the Harris's concept where he explained that the adaptive controller consists of the PID control term and the disturbance compensating term. The resulting controller's architecture is also found to be very similar to that of Wang's controller. This controller adds a self-tuning ability to the existing PID controller without replacing it by compensating the control errors through the neuro-controller. When applied to an actual magnetic levitation system which is known to be very nonlinear, it has also produced an excellent results.

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Auto-Tuning PID Control with Self-feedback Neurons (자기 궤환 뉴런을 가진 자동 동조 PID 제어)

  • Jung, Kyung-Kwon;Kim, Kyung-Soo;Gim, Ine;Eom, Ki-Hwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 1999.05a
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    • pp.348-354
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    • 1999
  • In recent years, a PID controller has been used as a major control method in real control processes. This controller requires a determination of PID control gains. But it is difficult to select the best gains theoretically. Thus there have been many approaches to determine them empirically Most of them are based on experience and knowledge. In this paper, we proposed a tuning method of the PID Parameters by using neural network. To show effectiveness of the proposed method, the simulation of DC motor and one link manipulator position control is carried out.

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MULTIVARIABLE WEIGHTED ADAPTIVE CONTROLLER DESIGN AND ITS APPLICATION

  • Lee, Kun-Yong
    • Proceedings of the KIEE Conference
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    • 1986.07a
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    • pp.132-135
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    • 1986
  • This paper shows that using the multivariable controller reduces the magnitude of fluctuations of the control signals which result improved control of the steam generator outputs. Comparison of the performance of the multivariable weighted adaptive controller(MWAC) with the performance of the existing PI controller and the self_tuning controller/1/, when the system goes through a transient mode, shows that the out-puts stay closer to their set points when they are controlled by the adaptive controller.

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Adaptive Control of Cell Recycled Continuous Bioreactor for Ethanol Production (에탄올 생산을 위한 세포재순환 연속 생물반응기의 적응제어)

  • 이재우;유영제
    • KSBB Journal
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    • v.6 no.3
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    • pp.263-270
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    • 1991
  • The optimal cell concentration and dilution rate for maximum ethanol productivity were obtained using dynamic simulation in cell recycled continuous bioreactor. The good control performance was observed using rule-based STR (self-tuning regulator) compared to conventional STR. Rule-base contained the scheme to implement the STR in an efficient on-off way and the scheme for the controlled variable to reach the optimal value in a short time. Since a mathematical model was used to analyze and estimate the changes of the state variables and the parameters, it was possible to understand the physical meaning of the system.

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An Application of Active Vision Head Control Using Model-based Compensating Neural Networks Controller

  • Kim, Kyung-Hwan;Keigo, Watanabe
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.168.1-168
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    • 2001
  • This article describes a novel model-based compensating neural network (NN) model developed to be used in our active binocular head controller, which addresses both the kinematics and dynamics aspects in trying to precisely track a moving object of interest to keep it in view. The compensating NN model is constructed using two classes of self-tuning neural models: namely Neural Gas (NG) algorithm and SoftMax function networks. The resultant servo controller is shown to be able to handle the tracking problem with a minimum knowledge of the dynamic aspects of the system.

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A controller design for direct drive arm robot using 32-Bit (MC 68020) CPU (32비트(MC 68020) CPU를 사용한 직접구동방식 로보트의 제어기 설계)

  • 이주장;윤형우;곽윤근
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10a
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    • pp.82-85
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    • 1988
  • This paper are the manufacture of controller of direct drive arm robot using 32 bit CPU(MC 69020). The work would draw on KIT of Robotics Laboratory whose extensive experience in 16 bit CPU Controller(MC 68008) in addition to the WHILE languages. We found that this controller is good for the direct drive arm robot controller for the use of self-tuning algorithms and real time control.

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Effectiveness of e-health systems in improving hypertension management and awareness: a systematic review

  • Alotaibi, Mohamed;Ammad uddin, Mohammad
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.1
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    • pp.173-187
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    • 2022
  • Recent studies have focused on self-management of hypertension using smart devices (cellular phones, tablets, watches). It has proven to be an effective tool for early detection and control of high Blood Pressure (BP) without affecting patients' daily routines. This systematic review surveys the existing self-monitoring systems, evaluate their effectiveness and compares the different approaches. We investigated the current systems in terms of various attributes, including methods used, sample size, type of investigation, inputs/ outputs, rate of success in controlling BP, group of users with higher response rate and beneficiaries, acceptability, and adherence to the system. We identified some limitations, shortcomings, and gaps in the research conducted recently studying the impact of mobile technology on managing hypertension. These shortcomings can generate future research opportunities and enable it to become more realistic and adaptive. We recommended including more observable factors and human behaviors that affect BP. Furthermore, we suggested that vital monitoring/logging and medication tuning are insufficient to improve hypertension control. There is also a need to observe and alter patient behavior and lifestyles.

Speed Control of Induction Motor Using Self-Learning Fuzzy Controller (자기학습형 퍼지제어기를 이용한 유도전동기의 속도제어)

  • 박영민;김덕헌;김연충;김재문;원충연
    • The Transactions of the Korean Institute of Power Electronics
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    • v.3 no.3
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    • pp.173-183
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    • 1998
  • In this paper, an auto-tuning method for fuzzy controller's membership functions based on the neural network is presented. The neural network emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and the reformed fuzzy controller uses for speed control of induction motor. Thus, in the case of motor parameter variation, the proposed method is superior to a conventional method in the respect of operation time and system performance. 32bit micro-processor DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzzy control algorithm. Through computer simulation and experimental results, it is confirmed that the proposed method can provide more improved control performance than that PI controller and conventional fuzzy controller.

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Analysis of Dynamic Positioning System Based on Self-Tuning Control (자기동조 제어기를 이용한 위치확보 시스템에 관한 연구)

  • Sang-M.,Lee;Pan-M.,Lee;Sa-Y.,Hong
    • Bulletin of the Society of Naval Architects of Korea
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    • v.26 no.2
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    • pp.32-40
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    • 1989
  • Dynamic ship positioning(DP) system is used to keep the position and heading of a ship, or a floating platform, above a pre-selected site on the seabed by using thrusters. This paper presents a control system based on filtering technique and optimal control theory. The planar motions of a vessel are assumed to consist of low frequency(LF) component and high frequency(HF) one. The former is mainly due to thrusters, current, wind and second order wave forces, while the latter is mainly due to first order oscillatory component of the wave force. Furthermore position measurement signals include the noise. By means of self-tuning filter and Kalman filter techniques, LF motion estimates and HF ones are seperately achieved from the position measurements of the vessel. The estimated LF motions are used as input to the feedback loops. The total thruster power is minimized using the Linear Quadratic Gaussian control theory. The performance of the vessel with the DP system is investigated by computer simulation.

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Development of Digital Gas Metal Arc Welding System and Welding Current Control Using Self-tuning Fuzzy PID

  • Doan, Phuc Thinh;Pratama, Pandu Sandi;Kim, Suk-Yoel;Kim, Hak-Kyeong;Yeun, Hwang-Yeong;Byun, Gi-Sig;Kim, Sang-Bong
    • Journal of Ocean Engineering and Technology
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    • v.25 no.6
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    • pp.1-8
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    • 2011
  • This paper describes a new method for a digital gas metal arc welding (GMAW) system. The GMAW system is an arc welding process that incorporates the GMAW power source (PS-GMAW) with a wire feed unit (WFU). The PS-GMAW requires an electric power of constant voltage. A constant magnitude is maintained for the arc current by controlling the wire-feed speed of the WFU. A mathematical model is derived, and a self-tuning fuzzy proportional-integral-derivative (PID) controller is designed and applied to control the welding current. The electrode wire feeding mechanism with this controller is driven by a DC motor, which can compensate for both the molten part of the electrode and undesirable fluctuations in the arc length during the welding process. By accurately maintaining the output welding current and welding voltage at constant values during the welding process, excellent welding results can be obtained. Simulation and experimental results are shown to prove the effectiveness of the proposed controller.