In this study, discrete time models of continuous time fractional order filters are obtained by using the Marine Predators Algorithm (MPA).
Marine Predators optimization algorithm is a population-based heuristic method. This method is inspired by the hunting behavior of marine predators. The algorithm works on three basic phases. These phases occur according to the difference or equality of the velocity of the prey and the predator. As it is known, uniform distribution is generally used in stochastic based optimization algorithms. However, in the MPA method, Brownian and Levy distributions are also used as well as uniform distribution.
First, continuous time frequency responses of fractional order filters are generated. Then, fourth order discrete time filters are designed that can give similar responses with generated continues time filter frequency responses. Ten parameters were optimized for the design of fourth order discrete time filters numerator and denominator. The Marine Predators method’s results are compared with the results of the Fractional order Darwinian Particle Swarm Optimization (FODPSO) algorithm, from which discrete time filters are obtained for two fractional order continuous time filter models. In this way, it has been shown comparatively that the Marine Predators Algorithm can be used in real engineering problems and can do filter discretization better.