Model order reduction by integral squared error minimization using bat algorithm

In this paper, a large order system is reduced by using the bat algorithm to a reduced-order approximant. The numerator and denominator coefficients of a desired reduced-order system are optimized based on integral square error minimization as an objective function pertaining to a unit-step as input. The efficacy of the proposed method is tested with three test systems to get a corresponding reduced-order system. The results are satisfactory in terms of minimum error with the proposed method as compared to Routh-Pade approximation and weighted-sum multiobjective harmony search based reduced models.