BAT algorithm for model order reduction

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Metaheuristic algorithms have made an unprecedented impact on model order reduction (MOR). Almost every year new algorithm emerges with an extended literature. These nature-based metaheuristic algorithms have attracted researchers to apply these algorithms for finding reduced order approximants of higher order system. This paper proposes a mixed approach for model order reduction based on metaheuristic BAT algorithm (BA) which is inspired by echolocation of microbats and Pade approximation based on matching of both time moments and Markov parameters. Further the efficiency of the method is investigated in terms of integral square error (ISE). This paper also draws a comparison of proposed method with existing techniques for models order reduction.