Model Order Reduction Method based on Improved Sine Cosine Algorithm

This paper presents an improved sine cosine algorithm (iSCA) for the reduction of high-order single-input single-output (SISO) systems. The proposed iSCA is adopted to solve the imbalance portion of the exploration and exploitation stages in the standard sine cosine algorithm (SCA). Specifically, a nonlinear decreasing updated gain is adopted to provide a proper balance of exploration and exploitation stages. The proposed iSCA is expected to yield a most accurate reduced-order model for a particular original high-order system by minimizing the integral square error (ISE) between their system output responses. The effectiveness of the proposed technique is evaluated by reducing a 6
^th
order double pendulum overhead crane model. The obtained simulation results revealed that the proposed iSCA is highly effective and remarkably consistent in obtaining an ideal reduced-order model compared to its original version.