Comparative Study of PSO and GWO Algorithms in Fractional-Order Low Pass Filter Design

This work, in an effort to improve the functionality and adaptability of electronic filters, is exploring the design of a Fractional Order Lowpass Filter by means of evolving algorithms. Filters’ fractional order transfer functions provide a more fluid representation of system dynamics than traditional integer order filter. Evolutionary algorithms are employed in the design phase to enhance the fractional-order filter’s parameters. Among the frequency response parameters that are optimized for are cut-off frequency, roll-off, and attenuation. Evolutionary algorithms are a useful tool for efficiently solving the difficult parameter space problems of fractional-order filters by swiftly identifying the optimal solutions. Through the examination of various filter configurations made possible by the algorithmic framework, designs that balance filter complexity and performance are found.