Application of genetic algorithms in the design of robust active filters

This work presents a design methodology for discrete active RC biquadratic filters based on genetic algorithm (GA). The main difference with other methods is the consideration of the passive sensitivities during the optimization process.The GA delivers the values of resistors and capacitors (from E series) that comply with the desired specifications and minimize at the same time the sensitivities. This characteristic leads to filters that exhibit low deviations in their functional parameters, despite drifts in the values of passive components. Additionally, the method allows the designer to establish the gain in the passband. In this way, it overcomes the problem of low gain values observed in some of the solutions given by other authors. The paper presents an evaluation campaign that considers 12 designs for showing the robustness of the method. This study analyses the results delivered by the GA at transfer function level using MATLAB. Subsequent evaluations validate these results by using SPICE simulations. Following these procedures, it is observed a proper matching between the behaviors of the filters predicted by the GA and the simulated ones. The performance comparison with other heuristics (solving the same problem) shows that our proposal is well suited for the design of active filters. The stochastic nature of the GA allows obtaining different design alternatives in each run. This feature gives the designer the possibility to choose between several options that are more appropriate for a particular design problem. The paper also provides a simple guideline for dealing with the results from the iterative executions of the GA. The design method requires tools that are usual to find in the industry. Practitioners can straightforwardly implement it, even those that are nonspecialists in heuristics.

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“…Also, the solutions have to be directly compatible with the industrial E series. Present authors report preliminary results in previous studies …”

Section: Introductionsupporting

confidence: 56%

Genetic algorithms applied to the design of robust biquadratic filters

Lovay

Romero

Peretti

2018

Int J Numerical Modelling

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“…Previous study (Lovay et al, 2015) Situation The above table shows the difference between these two studies despite the difference in the type of filter used, but the genetic algorithm gave better results in the current study in terms of reducing sensitivities of RC values.…”

Section: Current Studymentioning

confidence: 57%

“…There are very few studies that apply the genetic algorithm to the second-order active filter. Starting with a study by Lovay et al (2015), this study describes the application of the genetic algorithm to reduce sensitivities of second-order active filter called the SK (Sallen and Key) filter. The results show that configurations that meet established standards can be obtained.…”

Section: Introductionmentioning

confidence: 99%

Applying Genetic Algorithm to Optimization Second-Order Bandpass MGMFB Filter

Shukur¹,

Abttan²

2020

JST

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In this paper, we have applied the genetic algorithm to the selection of the true values for RC (resistors/capacitors) as an essential role in the development of analogue active filters. The classic method of incorporating passive elements is a complex situation and can attend to errors. In order to reduce the frequency of errors and the human effort, evolutionary optimization methods are employed to select the RC values. In this study, Genetic algorithm (GA) is proposed to optimize the second-order active filter. It must find the values of the passive elements RC to get a filter configuration that reduces the sensitivities to variations as well as reduces design errors less than a defined height value, concerning certain specifications. The optimization problem which is one of the problems that must be solved by GA is a multi-objective optimization problem (MOOP). GA was carried out taking into account two possible situations about the values that resistors and capacitors could adopt. The obtained experimental results show that GA can be used to obtain filter configurations that meet the specified standard.

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“…Bandpass filters and other more complicated filters will be tackled in the near future. Moreover, similar to Lovay et al, we plan to take into account the sensitivity of the filter's transfer function to the values of the passive components that should give more robust designs. This will be the subject of a separate future publication.…”

Section: Discussionmentioning

confidence: 99%

Optimal design of analog active filters using symbiotic organisms search

Dib

El-Asir

2018

Int J Numerical Modelling

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This paper investigates the optimal design of analog active filters using the symbiotic organisms search (SOS) algorithm. Symbiotic organisms search is a newly proposed global optimization method that is inspired by the symbiotic interaction strategies between different organisms in an ecosystem. In SOS, the 3 common types of symbiotic relationships (mutualism, commensalism, and parasitism) are modeled using simple expressions, which are used to find the global minimum of the fitness function. Unlike other methods, SOS is free of tuning parameters, which makes it an attractive optimization method. Here, SOS is used to determine the values of the passive components (resistors and capacitors) used in active filters. Two active filter topologies, fourth‐order Butterworth low‐pass filter and second‐order state variable low‐pass filter, are considered. The components values are chosen from several standard industrial series (E12, E24, and E96). The results obtained using SOS are compared with those obtained using several optimization methods, like particle swarm optimization, seeker optimization algorithm, differential evolution, and other ones. It is shown that the SOS is a robust straightforward evolutionary algorithm that can outperform other well‐known methods.

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Application of genetic algorithms in the design of robust active filters

Cited by 7 publications

References 8 publications

Genetic algorithms applied to the design of robust biquadratic filters

Genetic algorithms applied to the design of robust biquadratic filters

Applying Genetic Algorithm to Optimization Second-Order Bandpass MGMFB Filter

Optimal design of analog active filters using symbiotic organisms search

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