Application of Slime Mould Algorithm to Infinite Impulse Response System Identification Problem

Recently, the researchers working in the field of science and engineering have paid a considerable attention to the concept of the system identification to tackle with complex optimization problems. It is feasible to achieve more accurate models of physical plants with the infinite impulse response (IIR) models compared to their finite counterparts (FIR). To get the most out of the IIR models for the system identification, metaheuristic optimization algorithms can be used as efficient solutions. This work, therefore, aims to demonstrate more promising performance of a new metaheuristic algorithm named slime mould algorithm. In this regard, a comparative assessment is performed using different metaheuristic optimization techniques and different IIR model identification problems are considered. The slime mould algorithm is shown to achieve better accuracy and robustness in terms of IIR model identification with the help of obtained statistical results.