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Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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MathWorks Inc fuzzy logic controller flc
Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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Statcom Co Ltd d-statcom
Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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MathWorks Inc matlab/simulink
Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic <t>controller</t> <t>(PID-FLC)</t> The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.
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Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic controller (PID-FLC) The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.

Journal: Journal of Applied Research and Technology

Article Title: Comparative Study of PID, PD-FLC and PID-FLC for Active Magnetic Bearing

doi: 10.22201/icat.24486736e.2023.21.5.1875

Figure Lengend Snippet: Figure 9. Centroid method of defuzzification. 3.2.1. Designing of proportional integral derivative-fuzzy logic controller (PID-FLC) The designed FLC, shown in Figure 7 is a PD-FLC which can be modified to perform as a PID -FLC (Arun & Mohan 2018; Lai & Lin, 2003). Implementing an integrator to the output of PD-FLC and taking a summation of output of the integrator with output of PD- FLC becomes a PID-FLC (Li, 1997) as shown in Figure 10.

Article Snippet: Simulation of proposed active magnetic bearing (AMB) system with PD-FLC Fuzzy logic controller (FLC) is designed for the proposed system using fuzzy toolbox application of MATLAB (The MathWorks, 1998).

Techniques: Modification

Figure 10. A simplified PID-Fuzzy logic controller (PID-FLC). The designed PID-FLC is used as a position controller for the proposed AMB system, its performance is observed and compared with PD-FLC and PID controller. In the next section, different controllers will be simulated with the proposed AMB system, and their effect and performance are observed.

Journal: Journal of Applied Research and Technology

Article Title: Comparative Study of PID, PD-FLC and PID-FLC for Active Magnetic Bearing

doi: 10.22201/icat.24486736e.2023.21.5.1875

Figure Lengend Snippet: Figure 10. A simplified PID-Fuzzy logic controller (PID-FLC). The designed PID-FLC is used as a position controller for the proposed AMB system, its performance is observed and compared with PD-FLC and PID controller. In the next section, different controllers will be simulated with the proposed AMB system, and their effect and performance are observed.

Article Snippet: Simulation of proposed active magnetic bearing (AMB) system with PD-FLC Fuzzy logic controller (FLC) is designed for the proposed system using fuzzy toolbox application of MATLAB (The MathWorks, 1998).

Techniques:

Figure 18. Proposed AMB system (when inner closed loop is unity) with PD-FLC. Referring to Figure 2, the complete proposed AMB system is simulated in MATLAB with PD-FLC as a position controller as shown in Figure 19.

Journal: Journal of Applied Research and Technology

Article Title: Comparative Study of PID, PD-FLC and PID-FLC for Active Magnetic Bearing

doi: 10.22201/icat.24486736e.2023.21.5.1875

Figure Lengend Snippet: Figure 18. Proposed AMB system (when inner closed loop is unity) with PD-FLC. Referring to Figure 2, the complete proposed AMB system is simulated in MATLAB with PD-FLC as a position controller as shown in Figure 19.

Article Snippet: Simulation of proposed active magnetic bearing (AMB) system with PD-FLC Fuzzy logic controller (FLC) is designed for the proposed system using fuzzy toolbox application of MATLAB (The MathWorks, 1998).

Techniques: