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Integration of FOPID and Mayfly Algorithm for SEPIC with Multi-objective Functions

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Abstract SEPIC DC/DC with a single stage converter is organized in this work. Still, there is an energy loss of the single-ended primary-inductor converter (SEPIC), there is a need for deriving the new algorithmic model with modern concepts. A novel intelligent optimization algorithm namely mayfly algorithm is approached with unique optimization capabilities i.e. recently proposed. The topology of chosen controller has the conjunction of FOPID and Multi-objective Mayfly Algorithm (M2A), which is named as M2A-FOPID. To succeed this outcome from converter, an optimized FOPID can be utilized. The classic Fractional-Order Proportional-Integral-Derivative (FOPID) controller under single operating conditions with single objective optimization is expanded to a multi-objective configuration. An enhanced mayfly algorithm with FOPID depends upon the position of multi-objective functional group, which is incorporated in the above mentioned converter. The reference voltage of the controller is tuned and the generated PWM is optimized by the M2A-FOPID model, which can be applied to SEPIC. It provides an enthusiastic research value. On the other hand, there are some inadequate explorations, and also it may easily fall into the local optimization problem. The targets of this work can be able for boosting up the performance outcomes of the mayfly algorithm and this optimized value can find out its application in FOPID controller for multi-objective problems. To inaugurate the multi-objective FOPID (MO-FOPID) controller optimization issue under various multiple working situations, the integral of the time multiplied absolute error (ITAE) index at both high and low working condition is further comprised as objective functions. The M2A-FOPID is coupled to the SEPIC model and the mutual effectiveness of this controller with the combined model is experimentally tested. Also, the improvement of exploration is verified using the simulation model that is established in MATLAB /Simulink.
Research Square Platform LLC
Title: Integration of FOPID and Mayfly Algorithm for SEPIC with Multi-objective Functions
Description:
Abstract SEPIC DC/DC with a single stage converter is organized in this work.
Still, there is an energy loss of the single-ended primary-inductor converter (SEPIC), there is a need for deriving the new algorithmic model with modern concepts.
A novel intelligent optimization algorithm namely mayfly algorithm is approached with unique optimization capabilities i.
e.
recently proposed.
The topology of chosen controller has the conjunction of FOPID and Multi-objective Mayfly Algorithm (M2A), which is named as M2A-FOPID.
To succeed this outcome from converter, an optimized FOPID can be utilized.
The classic Fractional-Order Proportional-Integral-Derivative (FOPID) controller under single operating conditions with single objective optimization is expanded to a multi-objective configuration.
An enhanced mayfly algorithm with FOPID depends upon the position of multi-objective functional group, which is incorporated in the above mentioned converter.
The reference voltage of the controller is tuned and the generated PWM is optimized by the M2A-FOPID model, which can be applied to SEPIC.
It provides an enthusiastic research value.
On the other hand, there are some inadequate explorations, and also it may easily fall into the local optimization problem.
The targets of this work can be able for boosting up the performance outcomes of the mayfly algorithm and this optimized value can find out its application in FOPID controller for multi-objective problems.
To inaugurate the multi-objective FOPID (MO-FOPID) controller optimization issue under various multiple working situations, the integral of the time multiplied absolute error (ITAE) index at both high and low working condition is further comprised as objective functions.
The M2A-FOPID is coupled to the SEPIC model and the mutual effectiveness of this controller with the combined model is experimentally tested.
Also, the improvement of exploration is verified using the simulation model that is established in MATLAB /Simulink.

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