Squirrel Search Optimization Algorithm for Order Abatement of SISO Linear Time Invariant Systems

The article addresses the critical challenges in model order reduction for complex systems, focusing on the application of the Squirrel Search Optimization Algorithm (SSOA) to Single Input Single Output (SISO) Linear Time Invariant (LTI) systems. It begins by outlining the necessity of order abatement techniques to simplify higher-order systems for real-time applications, highlighting the limitations of traditional methods. The core of the article introduces the SSOA, a bio-inspired algorithm modeled after the foraging and gliding behaviors of southern flying squirrels. This innovative approach is detailed through its mathematical formulation and implementation steps, emphasizing its effectiveness in minimizing cost functions such as Integral Square Error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Error (ITAE). The article presents two comprehensive examples, demonstrating the application of SSOA to reduce the order of high-order LTI systems while maintaining the original system's response characteristics. Through detailed comparisons with existing techniques, the article showcases the superior performance of SSOA in terms of step, frequency, and impulse responses, as well as various performance indices. The results underscore the algorithm's ability to achieve faster convergence and higher accuracy, making it a promising tool for engineers and researchers in the field of control systems and optimization.