The Experts below are selected from a list of 21174 Experts worldwide ranked by ideXlab platform

Engin Yesil - One of the best experts on this subject based on the ideXlab platform.

  • self tuning fuzzy pid type load and frequency controller
    Energy Conversion and Management, 2004
    Co-Authors: Engin Yesil, Mujde Guzelkaya, Ibrahim Eksin
    Abstract:

    In this paper, a self tuning fuzzy PID type controller is proposed for solving the load frequency control (LFC) problem. The fuzzy PID type controller is constructed as a set of control rules, and the control signal is directly deduced from the knowledge base and the fuzzy inference. Moreover, there exists a self tuning mechanism that adjusts the input scaling factor corresponding to the derivative Coefficient and the output scaling factor corresponding to the Integral Coefficient of the PID type fuzzy logic controller in an on-line manner. The self tuning mechanism depends on the peak observer idea, and this idea is modified and adapted to the LFC problem. A two area interconnected system is assumed for demonstrations. The proposed self tuning fuzzy PID type controller has been compared with the fuzzy PID type controller without a self tuning mechanism and the conventional Integral controller through some performance indices.

  • self tuning of pid type fuzzy logic controller Coefficients via relative rate observer
    Engineering Applications of Artificial Intelligence, 2003
    Co-Authors: Mujde Guzelkaya, Ibrahim Eksin, Engin Yesil
    Abstract:

    Abstract In this study, a new method is proposed for tuning the Coefficients of PID-type fuzzy logic controllers (FLCs). The new method adjusts the input scaling factor corresponding to the derivative Coefficient and the output scaling factor corresponding to the Integral Coefficient of the PID-type FLC using a fuzzy inference mechanism in an on-line manner. The fuzzy inference mechanism that adjusts the related Coefficients has two inputs, one of which is called “normalized acceleration” and the other one is the classical “error”. The “normalized acceleration” gives the “relative rate” information about the fastness or slowness of the system response. An appropriate rule-base is generated for the adaptation of the derivative Coefficient of the PID-type FLC using these two input variables. The Integral Coefficient is then updated as the reciprocal of the derivative Coefficient. The robustness and effectiveness of the new self-tuning algorithm have been compared with the other related tuning methods proposed in the literature through simulations. The simulations are done on a second-order system with varying parameters and time delay.

Ibrahim Eksin - One of the best experts on this subject based on the ideXlab platform.

  • self tuning fuzzy pid type load and frequency controller
    Energy Conversion and Management, 2004
    Co-Authors: Engin Yesil, Mujde Guzelkaya, Ibrahim Eksin
    Abstract:

    In this paper, a self tuning fuzzy PID type controller is proposed for solving the load frequency control (LFC) problem. The fuzzy PID type controller is constructed as a set of control rules, and the control signal is directly deduced from the knowledge base and the fuzzy inference. Moreover, there exists a self tuning mechanism that adjusts the input scaling factor corresponding to the derivative Coefficient and the output scaling factor corresponding to the Integral Coefficient of the PID type fuzzy logic controller in an on-line manner. The self tuning mechanism depends on the peak observer idea, and this idea is modified and adapted to the LFC problem. A two area interconnected system is assumed for demonstrations. The proposed self tuning fuzzy PID type controller has been compared with the fuzzy PID type controller without a self tuning mechanism and the conventional Integral controller through some performance indices.

  • self tuning of pid type fuzzy logic controller Coefficients via relative rate observer
    Engineering Applications of Artificial Intelligence, 2003
    Co-Authors: Mujde Guzelkaya, Ibrahim Eksin, Engin Yesil
    Abstract:

    Abstract In this study, a new method is proposed for tuning the Coefficients of PID-type fuzzy logic controllers (FLCs). The new method adjusts the input scaling factor corresponding to the derivative Coefficient and the output scaling factor corresponding to the Integral Coefficient of the PID-type FLC using a fuzzy inference mechanism in an on-line manner. The fuzzy inference mechanism that adjusts the related Coefficients has two inputs, one of which is called “normalized acceleration” and the other one is the classical “error”. The “normalized acceleration” gives the “relative rate” information about the fastness or slowness of the system response. An appropriate rule-base is generated for the adaptation of the derivative Coefficient of the PID-type FLC using these two input variables. The Integral Coefficient is then updated as the reciprocal of the derivative Coefficient. The robustness and effectiveness of the new self-tuning algorithm have been compared with the other related tuning methods proposed in the literature through simulations. The simulations are done on a second-order system with varying parameters and time delay.

Mujde Guzelkaya - One of the best experts on this subject based on the ideXlab platform.

  • self tuning fuzzy pid type load and frequency controller
    Energy Conversion and Management, 2004
    Co-Authors: Engin Yesil, Mujde Guzelkaya, Ibrahim Eksin
    Abstract:

    In this paper, a self tuning fuzzy PID type controller is proposed for solving the load frequency control (LFC) problem. The fuzzy PID type controller is constructed as a set of control rules, and the control signal is directly deduced from the knowledge base and the fuzzy inference. Moreover, there exists a self tuning mechanism that adjusts the input scaling factor corresponding to the derivative Coefficient and the output scaling factor corresponding to the Integral Coefficient of the PID type fuzzy logic controller in an on-line manner. The self tuning mechanism depends on the peak observer idea, and this idea is modified and adapted to the LFC problem. A two area interconnected system is assumed for demonstrations. The proposed self tuning fuzzy PID type controller has been compared with the fuzzy PID type controller without a self tuning mechanism and the conventional Integral controller through some performance indices.

  • self tuning of pid type fuzzy logic controller Coefficients via relative rate observer
    Engineering Applications of Artificial Intelligence, 2003
    Co-Authors: Mujde Guzelkaya, Ibrahim Eksin, Engin Yesil
    Abstract:

    Abstract In this study, a new method is proposed for tuning the Coefficients of PID-type fuzzy logic controllers (FLCs). The new method adjusts the input scaling factor corresponding to the derivative Coefficient and the output scaling factor corresponding to the Integral Coefficient of the PID-type FLC using a fuzzy inference mechanism in an on-line manner. The fuzzy inference mechanism that adjusts the related Coefficients has two inputs, one of which is called “normalized acceleration” and the other one is the classical “error”. The “normalized acceleration” gives the “relative rate” information about the fastness or slowness of the system response. An appropriate rule-base is generated for the adaptation of the derivative Coefficient of the PID-type FLC using these two input variables. The Integral Coefficient is then updated as the reciprocal of the derivative Coefficient. The robustness and effectiveness of the new self-tuning algorithm have been compared with the other related tuning methods proposed in the literature through simulations. The simulations are done on a second-order system with varying parameters and time delay.

Qian Z. - One of the best experts on this subject based on the ideXlab platform.

  • A rapid and accurate technique with updating strategy for surface defect inspection of pipelines
    'Institute of Electrical and Electronics Engineers (IEEE)', 2021
    Co-Authors: Da Y., Wang B., Liu Dianzi, Qian Z.
    Abstract:

    Defect inspection in pipes at the early stage is of crucial importance to maintain the ongoing safety and suitability of the equipment before it presents an unacceptable risk. Due to the nature of detection methods being costly or complex, the efficiency and accuracy of results obtained hardly meet the requirements from industries. To explore a rapid and accurate technique for surface defects detection, a novel approach QDFT (Quantitative Detection of Fourier Transform) has been recently proposed by authors to efficiently reconstruct defects. However, the accuracy of this approach needs to be further improved. In this paper, a modified QDFT method with integration of an Integral Coefficient updating strategy, called QDFTU (quantitative detection of Fourier transform of updating), is developed to reconstruct the defect profile with a high level of accuracy throughout iterative calculations of Integral Coefficients from the reference model updated by a termination criteria (RMSE, root mean square error). Moreover, dispersion equations of circumferential guided waves in pipes are derived in the helical coordinate to accommodate the stress and displacement calculations in the scattered field using hybrid FEM. To demonstrate the superiority of the developed QDFTU in terms of accuracy and efficiency, four types of defect profiles, i.e., a rectangular flaw, a multi-step flaw, a double-rectangular flaw, and a triple-rectangular flaw, are examined. Results show the fast convergence of QDFTU can be identified by no more than three updates for each case and its high accuracy is observed by a smallest difference between the predicted defect profile and the real one in terms of mean absolute percentage error (MSPE) value, which is 6.69% in the rectangular-flaw detection example

  • A rapid and accurate technique with updating strategy for surface defect inspection of pipelines
    'Institute of Electrical and Electronics Engineers (IEEE)', 2021
    Co-Authors: Da Y., Wang B., Liu Dianzi, Qian Z.
    Abstract:

    Defect inspection in pipes at the early stage is of crucial importance to maintain the ongoing safety and suitability of the equipment before it presents an unacceptable risk. Due to the nature of detection methods being costly or complex, the efficiency and accuracy of results obtained hardly meet the requirements from industries. To explore a rapid and accurate technique for surface defects detection, a novel approach QDFT (Quantitative Detection of Fourier Transform) has been recently proposed by authors to efficiently reconstruct defects. However, the accuracy of this approach needs to be further improved. In this paper, a modified QDFT method with integration of an Integral Coefficient updating strategy, called as QDFTU, is developed to reconstruct the defect profile with a high level of accuracy throughout iterative calculations of Integral Coefficients from the reference model updated by a termination criteria (RMSE, root mean square error). Moreover, dispersion equations of circumferential guided waves in pipes are derived in the helical coordinate to accommodate the stress and displacement calculations in the scattered field using hybrid FEM. To demonstrate the superiority of the developed QDFTU in terms of accuracy and efficiency, four types of defect profiles, i.e., a rectangular flaw, a multi-step flaw, a double-rectangular flaw, and a triple-rectangular flaw, are examined. Results show the fast convergence of QDFTU can be identified by no more than three updates for each case and its high accuracy is observed by a smallest difference between the predicted defect profile and the real one in terms of mean absolute percentage error (MSPE) value, which is 6.69% in the rectangular-flaw detection example

Youyin Jing - One of the best experts on this subject based on the ideXlab platform.

  • fuzzy immune self tuning pid control of hvac system
    International Conference on Mechatronics and Automation, 2008
    Co-Authors: Jiangjiang Wang, Chunfa Zhang, Youyin Jing
    Abstract:

    Aiming at the non-linear links such as time lag, large inertia, in the heating, ventilating, and air conditioning (HVAC) system, a fuzzy immune self-tuning PID control system is designed. With ideas from the biological immune system, fuzzy immune PID control strategy is applied to central air-conditioning system, in which the proportional Coefficient of PID is adaptively modulated by means of fuzzy immune algorithm, and Integral Coefficient and differential Coefficient are dynamically regulated by fuzzy logic scheme. Based on the model of central air-conditioning room, the simulation investigation has been carried out and the result shows validity of the control scheme and improvement in dynamic performance and robustness of central air-conditioning control system.