A Critical Review of Pole Clustering Techniques: Common Pitfalls, Extension to MIMO and New Enhanced Variant of the Cuckoo Search Algorithm

Abstract

ABSTRACT This article presents a critical review of classical and modern pole clustering techniques for model order reduction in high‐order systems. It highlights key limitations and common pitfalls encountered in traditional approaches, especially when extended to Multi‐Input Multi‐Output (MIMO) systems. In response, we propose an enhanced variant of the Cuckoo Search Algorithm (CSA), incorporating Lévy flight to improve global exploration and solution quality. This new metaheuristic strategy is evaluated against benchmark cases and applied to a real‐world methanisation process model. Simulation results demonstrate superior performance in terms of accuracy and convergence compared to existing reduction techniques. The proposed method maintains essential dynamic characteristics while achieving a significant reduction in model complexity, offering a promising direction for control and simulation of complex dynamical systems.