Model Order Reduction based on meta-heuristic optimization methods

In the real world, most of physical systems have complex high order models. This kind of complexity causes some difficulties in all aspects of analysis, simulation and control. The main idea of the model order reduction is to provide a low order system model and therefore a low order system controller which may have less hardware requirements. This paper presents a new approach for model order reduction based on optimizing the Pade rational approximator to solve the complex model reduction problems The numerator and denominator polynomial of the reduced order model are achieved by minimizing the Integral Square error of the step response between the original high order and reduced order system using World Cup Optimization Algorithm. Meta-heuristic algorithms guarantee the reduced order model system stability if the original high order model is stable. the proposed method illustrated through numerical example from literature and the

Pade Approximation; Transfer Function; World Cup Optimization Algorithm; PSO; QIWO; Pade Integral Square Error