Model Order Reduction Using Cuckoo Search Optimization Technique

An optimization technique is introduced to reduce a system of high order by using Cuckoo Search Optimization (CSO). The numerator and denominator coefficient parameters of proposed system are defined by Cuckoo search optimization (CSO). In this paper, numerical examples of linear time invariant system are illustrated and proposed method efficacy is tested and compared to Eigen spectrum-factor division analysis, hybrid balanced truncation method, pole clustering with Routh-Pade Approximation, multi objective harmony search and other relative techniques. CSO technique provides an optimal order reduction model and minimizes the integral square error. The establishment of satisfactory result of proposed method for higher order model displayed by step response and Bode diagram and better perfection with minimized ISE error related to comparable newly developed mixed technology is obtained. All the observations are studied in MATLAB.