Performance Analysis for Fractional Order Fuzzy PID Controller: A Comparative Study with Various PID Controller Structures

Elsheikh, Emad A.; Abdo, Mohamed I.

doi:10.1109/icenco55801.2022.10032464

Cited by 1 publication

(3 citation statements)

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“…The parameters of the PID controller, namely K p , K i , and K d , must be defined appropriately. In the case of 2DOFPID, in addition to these, b and c values also need to be specified, and for In this case, the system operates more efficiently as intended [11,12].…”

Section: Contributionsmentioning

confidence: 99%

“…Here, U(s) is the control signal and E(s) is the error signal [48,49]. The fractional-order system can be represented by an nterm non-homogeneous fractional-order differential equation, as shown in Equation (11). Here, the Caputo fractional derivative of order is D 𝛼 = 0 D 𝛼 t .…”

Section: Pid 2dofpid and Fopid Controllersmentioning

confidence: 99%

“…By correctly determining these values, controllers that operate at the desired speed have negligible or no overshoot and are capable of nullifying errors. In this case, the system operates more efficiently as intended [11, 12].…”

Section: Introductionmentioning

confidence: 99%

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Exploring solar energy systems: A comparative study of optimization algorithms, MPPTs, and controllers

Güven

2024

IET Control Theory & Appl

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This study elucidates the use of optimization algorithms to identify the controller parameters employed in adjusting the current and voltage values of loads powered by solar energy systems and battery groups. Parameters for these controllers were independently derived using a combination of ant colony optimization with Levy flight, hybrid firefly‐particle swarm optimization, hybrid gravitation search algorithm‐particle swarm optimization, alongside the implementation of Jaya and whale optimization algorithms. The results from each method were juxtaposed for thorough analysis. In addition, three distinct Maximum Power Point Tracker (MPPT) algorithms were employed in the system: perturbation and observation, open circuit voltage, and incremental conductance (IC). To assess the system’s adaptability to real‐world conditions, it was tested against varying temperatures and sunlight levels. Moreover, potential changes in the loads were considered by varying the load. The efficacy of the controllers was examined by altering both the environment and load. The effectiveness of the controllers was examined by referring to the integral of time‐weighted absolute error value. The system was simulated using MATLAB/Simulink software. This study demonstrates that the fractional‐order PID controller achieves the most effective results, the Jaya algorithm provides the best controller parameters, and the IC technique exhibits the highest performance in MPPT.

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Section: Contributionsmentioning

confidence: 99%