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anfis controller main parts  (MathWorks Inc)


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    MathWorks Inc anfis controller main parts
    Fig. 9. Configuration of <t>ANFIS</t> <t>Controller</t> main parts in Simulink environment.
    Anfis Controller Main Parts, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 873 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/anfis controller main parts/product/MathWorks Inc
    Average 96 stars, based on 873 article reviews
    anfis controller main parts - by Bioz Stars, 2026-04
    96/100 stars

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    1) Product Images from "Novel technique for precise derating torque of induction motors using ANFIS."

    Article Title: Novel technique for precise derating torque of induction motors using ANFIS.

    Journal: Scientific reports

    doi: 10.1038/s41598-025-92821-z

    Fig. 9. Configuration of ANFIS Controller main parts in Simulink environment.
    Figure Legend Snippet: Fig. 9. Configuration of ANFIS Controller main parts in Simulink environment.

    Techniques Used:



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    Fig. 9. Configuration of ANFIS Controller main parts in Simulink environment.

    Journal: Scientific reports

    Article Title: Novel technique for precise derating torque of induction motors using ANFIS.

    doi: 10.1038/s41598-025-92821-z

    Figure Lengend Snippet: Fig. 9. Configuration of ANFIS Controller main parts in Simulink environment.

    Article Snippet: Configuration of ANFIS Controller main parts in Simulink environment.

    Techniques:

    Fig. 4. Membership functions and value gaps of CF1 and CFac of the input variables of ANFIS. (a) Input membership functions, CF1 and (b) input membership functions, CFac.

    Journal: Ain Shams Engineering Journal

    Article Title: NERC’s control performance standards based load frequency controller for a multi area deregulated power system with ANFIS approach

    doi: 10.1016/j.asej.2017.05.006

    Figure Lengend Snippet: Fig. 4. Membership functions and value gaps of CF1 and CFac of the input variables of ANFIS. (a) Input membership functions, CF1 and (b) input membership functions, CFac.

    Article Snippet: The basic steps for the ANFIS controller design in MATLAB/ Simulink environment (Fig. 1) are mentioned below [6,27] (1) Model and simulate the test system with simulink and fuzzy logic controller with the given rule base. (2) Collect the training data while simulating the model with fuzzy logic controller. (3) The two inputs, i.e., CF1 and CFac and the output signal provides the training data. (4) Use anfisedit to generate the ANFIS .fis file. (5) Arrange the training data collected in Step 2 and generate the FIS with Gaussian membership function. (6) Trains the collected data with the generated FIS up to a par- ticular no. of Epochs. (7) Save the FIS.

    Techniques:

    Fig. 11. Excess raise/lower signals of GENCO-1 with three different controllers. (a) Speed changer raise/lower signals of GENCO-1 with three different controllers. (b) Excess raise/lower signals of GENCO-1 of PID controller over NERC standards-based ANFIS controller. (c) Excess raise/lower signals of GENCO-1 of ANFIS controller over NERC standards-based ANFIS controller.

    Journal: Ain Shams Engineering Journal

    Article Title: NERC’s control performance standards based load frequency controller for a multi area deregulated power system with ANFIS approach

    doi: 10.1016/j.asej.2017.05.006

    Figure Lengend Snippet: Fig. 11. Excess raise/lower signals of GENCO-1 with three different controllers. (a) Speed changer raise/lower signals of GENCO-1 with three different controllers. (b) Excess raise/lower signals of GENCO-1 of PID controller over NERC standards-based ANFIS controller. (c) Excess raise/lower signals of GENCO-1 of ANFIS controller over NERC standards-based ANFIS controller.

    Article Snippet: The basic steps for the ANFIS controller design in MATLAB/ Simulink environment (Fig. 1) are mentioned below [6,27] (1) Model and simulate the test system with simulink and fuzzy logic controller with the given rule base. (2) Collect the training data while simulating the model with fuzzy logic controller. (3) The two inputs, i.e., CF1 and CFac and the output signal provides the training data. (4) Use anfisedit to generate the ANFIS .fis file. (5) Arrange the training data collected in Step 2 and generate the FIS with Gaussian membership function. (6) Trains the collected data with the generated FIS up to a par- ticular no. of Epochs. (7) Save the FIS.

    Techniques:

    Fig. 12. Excess raise/lower signals of Genco-2 with three different controllers. (a) Speed changer raise/lower signals of GENCO-2 with three different controllers. (b) Excess raise/lower signals of GENCO-2 of PID controller over NERC standards-based ANFIS controller. (c) Excess raise/lower signals of GENCO-2 of ANFIS controller over NERC standards-based ANFIS controller.

    Journal: Ain Shams Engineering Journal

    Article Title: NERC’s control performance standards based load frequency controller for a multi area deregulated power system with ANFIS approach

    doi: 10.1016/j.asej.2017.05.006

    Figure Lengend Snippet: Fig. 12. Excess raise/lower signals of Genco-2 with three different controllers. (a) Speed changer raise/lower signals of GENCO-2 with three different controllers. (b) Excess raise/lower signals of GENCO-2 of PID controller over NERC standards-based ANFIS controller. (c) Excess raise/lower signals of GENCO-2 of ANFIS controller over NERC standards-based ANFIS controller.

    Article Snippet: The basic steps for the ANFIS controller design in MATLAB/ Simulink environment (Fig. 1) are mentioned below [6,27] (1) Model and simulate the test system with simulink and fuzzy logic controller with the given rule base. (2) Collect the training data while simulating the model with fuzzy logic controller. (3) The two inputs, i.e., CF1 and CFac and the output signal provides the training data. (4) Use anfisedit to generate the ANFIS .fis file. (5) Arrange the training data collected in Step 2 and generate the FIS with Gaussian membership function. (6) Trains the collected data with the generated FIS up to a par- ticular no. of Epochs. (7) Save the FIS.

    Techniques:

    Fig. 13. Excess raise/lower signals of GENCO-3 with three different controllers. (a) Speed changer raise/lower signals of GENCO-3 with three different controllers. (b) Excess raise/lower signals of GENCO-3 of PID controller over NERC standards-based ANFIS controller. (c) Excess raise/lower signals of GENCO-3 of ANFIS controller over NERC standards-based ANFIS controller.

    Journal: Ain Shams Engineering Journal

    Article Title: NERC’s control performance standards based load frequency controller for a multi area deregulated power system with ANFIS approach

    doi: 10.1016/j.asej.2017.05.006

    Figure Lengend Snippet: Fig. 13. Excess raise/lower signals of GENCO-3 with three different controllers. (a) Speed changer raise/lower signals of GENCO-3 with three different controllers. (b) Excess raise/lower signals of GENCO-3 of PID controller over NERC standards-based ANFIS controller. (c) Excess raise/lower signals of GENCO-3 of ANFIS controller over NERC standards-based ANFIS controller.

    Article Snippet: The basic steps for the ANFIS controller design in MATLAB/ Simulink environment (Fig. 1) are mentioned below [6,27] (1) Model and simulate the test system with simulink and fuzzy logic controller with the given rule base. (2) Collect the training data while simulating the model with fuzzy logic controller. (3) The two inputs, i.e., CF1 and CFac and the output signal provides the training data. (4) Use anfisedit to generate the ANFIS .fis file. (5) Arrange the training data collected in Step 2 and generate the FIS with Gaussian membership function. (6) Trains the collected data with the generated FIS up to a par- ticular no. of Epochs. (7) Save the FIS.

    Techniques:

    Fig. 14. Excess raise/lower signals of GENCO-4 with three different controllers. (a) Speed changer raise/lower signals of GENCO-4 with three different controllers. (b) Excess raise/lower signals of GENCO-4 of PID controller over NERC standards-based ANFIS controller. (c) Excess raise/lower signals of GENCO-4 of ANFIS controller over NERC standards-based ANFIS controller.

    Journal: Ain Shams Engineering Journal

    Article Title: NERC’s control performance standards based load frequency controller for a multi area deregulated power system with ANFIS approach

    doi: 10.1016/j.asej.2017.05.006

    Figure Lengend Snippet: Fig. 14. Excess raise/lower signals of GENCO-4 with three different controllers. (a) Speed changer raise/lower signals of GENCO-4 with three different controllers. (b) Excess raise/lower signals of GENCO-4 of PID controller over NERC standards-based ANFIS controller. (c) Excess raise/lower signals of GENCO-4 of ANFIS controller over NERC standards-based ANFIS controller.

    Article Snippet: The basic steps for the ANFIS controller design in MATLAB/ Simulink environment (Fig. 1) are mentioned below [6,27] (1) Model and simulate the test system with simulink and fuzzy logic controller with the given rule base. (2) Collect the training data while simulating the model with fuzzy logic controller. (3) The two inputs, i.e., CF1 and CFac and the output signal provides the training data. (4) Use anfisedit to generate the ANFIS .fis file. (5) Arrange the training data collected in Step 2 and generate the FIS with Gaussian membership function. (6) Trains the collected data with the generated FIS up to a par- ticular no. of Epochs. (7) Save the FIS.

    Techniques: