The JAYA method, a population-based metaheuristic optimization approach, is used in this study to present the design of a digital finite impulse response fractional order differentiator (FIRFOD). The design seeks to identify such ideal differentiator coefficients that minimize their absolute errors with the desired ideal differentiator response. The extensive simulation results and Wilcoxon rank-sum test at 99% level of confidence show how well JAYA algorithm performs better in finding the best coefficients of digital FIR-FOD in comparison with Cuckoo Search Algorithm (CSA) and Particle Swarm Optimization (PSO). Because it has no dependency on method-specific parameters, the JAYA algorithm achieves faster convergence than the CSA and PSO algorithms for this design problem.

Fractional calculus, Finite Impulse response, Differentiator, Fitness, Metaheuristics