Deterministic and Stochastic Analysis of Fractional-Order Legendre Filter with Uncertain Parameters

Fractional order filters are increasingly used due to their flexibility and continuous stepped stopband attenuation rate. The current work presents a deterministic design plan for an optimal fractional-order Legendre low-pass filter along with a stochastic investigation of its parametric uncertainty...

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Main Authors: Mohammed A. Hassan, Andrew Amgad, Osama H. Galal
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Fractal and Fractional
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Online Access:https://www.mdpi.com/2504-3110/8/11/645
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author Mohammed A. Hassan
Andrew Amgad
Osama H. Galal
author_facet Mohammed A. Hassan
Andrew Amgad
Osama H. Galal
author_sort Mohammed A. Hassan
collection DOAJ
description Fractional order filters are increasingly used due to their flexibility and continuous stepped stopband attenuation rate. The current work presents a deterministic design plan for an optimal fractional-order Legendre low-pass filter along with a stochastic investigation of its parametric uncertainty. First, the filter’s order was determined using the provided parameters, then the flower pollination algorithm was used to tune the transfer function parameters. This method uses the phase delay and magnitude response functions to quantify the desired output. Circuit diagrams, LT spice simulations, and a case study were used to validate the method. In addition, the effects of various components on stability and the performance metrics were further examined. Next, each of the described fractional system parameters (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>R</mi><mn>1</mn></msub></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>R</mi><mn>2</mn></msub></semantics></math></inline-formula>, the ratio <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mstyle scriptlevel="0" displaystyle="true"><mfrac><msub><mi>R</mi><mn>4</mn></msub><msub><mi>R</mi><mn>3</mn></msub></mfrac></mstyle></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>C</mi><mi>α</mi></msub></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>C</mi><mi>β</mi></msub></semantics></math></inline-formula>) was modeled as an uncertain term in a distinct cases, referred to as Cases I–V, respectively, and their combined effect was investigated as Case VI. These uncertain parameters were implemented using both random variables and stochastic processes. The system response was assessed using the Monte Carlo simulation method, and the mean, standard deviation, probability density function, and lower and upper bounds were plotted. Additionally, the key statistics of the cutoff frequency were tabulated in all cases. Many findings are addressed by the provided system solutions; briefly, the results revealed that the impact of uncertainty cases on system response, in descending order, was Case VI, Case III, Case V, Case II, Case I, and Case IV. Furthermore, the system demonstrated instability in Cases III and VI, which drew the designers’ attention to these two cases.
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spelling doaj-art-4607264017e44c73ad664961fae48c3a2024-11-26T18:05:01ZengMDPI AGFractal and Fractional2504-31102024-10-0181164510.3390/fractalfract8110645Deterministic and Stochastic Analysis of Fractional-Order Legendre Filter with Uncertain ParametersMohammed A. Hassan0Andrew Amgad1Osama H. Galal2Electrical Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 63514, EgyptEngineering Mathematics and Physics Department, Faculty of Engineering, Fayoum University, Fayoum 63514, EgyptEngineering Mathematics and Physics Department, Faculty of Engineering, Fayoum University, Fayoum 63514, EgyptFractional order filters are increasingly used due to their flexibility and continuous stepped stopband attenuation rate. The current work presents a deterministic design plan for an optimal fractional-order Legendre low-pass filter along with a stochastic investigation of its parametric uncertainty. First, the filter’s order was determined using the provided parameters, then the flower pollination algorithm was used to tune the transfer function parameters. This method uses the phase delay and magnitude response functions to quantify the desired output. Circuit diagrams, LT spice simulations, and a case study were used to validate the method. In addition, the effects of various components on stability and the performance metrics were further examined. Next, each of the described fractional system parameters (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>R</mi><mn>1</mn></msub></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>R</mi><mn>2</mn></msub></semantics></math></inline-formula>, the ratio <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mstyle scriptlevel="0" displaystyle="true"><mfrac><msub><mi>R</mi><mn>4</mn></msub><msub><mi>R</mi><mn>3</mn></msub></mfrac></mstyle></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>C</mi><mi>α</mi></msub></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>C</mi><mi>β</mi></msub></semantics></math></inline-formula>) was modeled as an uncertain term in a distinct cases, referred to as Cases I–V, respectively, and their combined effect was investigated as Case VI. These uncertain parameters were implemented using both random variables and stochastic processes. The system response was assessed using the Monte Carlo simulation method, and the mean, standard deviation, probability density function, and lower and upper bounds were plotted. Additionally, the key statistics of the cutoff frequency were tabulated in all cases. Many findings are addressed by the provided system solutions; briefly, the results revealed that the impact of uncertainty cases on system response, in descending order, was Case VI, Case III, Case V, Case II, Case I, and Case IV. Furthermore, the system demonstrated instability in Cases III and VI, which drew the designers’ attention to these two cases.https://www.mdpi.com/2504-3110/8/11/645fractional Legendre filtermetaheuristicfractional Legendre polynomialstochastic fractional systemuncertain parametersMCS
spellingShingle Mohammed A. Hassan
Andrew Amgad
Osama H. Galal
Deterministic and Stochastic Analysis of Fractional-Order Legendre Filter with Uncertain Parameters
Fractal and Fractional
fractional Legendre filter
metaheuristic
fractional Legendre polynomial
stochastic fractional system
uncertain parameters
MCS
title Deterministic and Stochastic Analysis of Fractional-Order Legendre Filter with Uncertain Parameters
title_full Deterministic and Stochastic Analysis of Fractional-Order Legendre Filter with Uncertain Parameters
title_fullStr Deterministic and Stochastic Analysis of Fractional-Order Legendre Filter with Uncertain Parameters
title_full_unstemmed Deterministic and Stochastic Analysis of Fractional-Order Legendre Filter with Uncertain Parameters
title_short Deterministic and Stochastic Analysis of Fractional-Order Legendre Filter with Uncertain Parameters
title_sort deterministic and stochastic analysis of fractional order legendre filter with uncertain parameters
topic fractional Legendre filter
metaheuristic
fractional Legendre polynomial
stochastic fractional system
uncertain parameters
MCS
url https://www.mdpi.com/2504-3110/8/11/645
work_keys_str_mv AT mohammedahassan deterministicandstochasticanalysisoffractionalorderlegendrefilterwithuncertainparameters
AT andrewamgad deterministicandstochasticanalysisoffractionalorderlegendrefilterwithuncertainparameters
AT osamahgalal deterministicandstochasticanalysisoffractionalorderlegendrefilterwithuncertainparameters