Inclined planes system optimization: Theory, literature review, and state-of-the-art versions for IIR system identification.

[Display omitted] • An literature review on IPO, IIR system identification, and combining the two. • Introducing an state-of-the-art version called IIPO. • Evaluation of IIPO and SIPO versions for the first time to design IIR filters. • Successful performance of the proposed methods via a proper fitness and two controls. • Proving the efficiency, stability, and reliability by 100 independent trials. The Inclined Planes System Optimization (IPO) algorithm is recent algorithm that uses Newton's second law to perform optimization. After conducting a thorough literature review, this paper proposes an improved version of IPO called IIPO. This improvement is achieved by changing exploratory and exploitative behavior of the standard IPO proportional to the progress of optimization (iteration). The IIPO is employed for optimizing IIR digital filter design, which is a challenging engineering problem. Adaptive IIR modeling as a multimodal optimization problem is designed and developed under system identification structure with an appropriate single-objective function in the frequency domain. Implementations are performed in both modeling cases with same and reduced orders, and under two identification forms with and without environmental additive noise. The results are reported along with various analyzes compared to a wide range of IPO variants. The statistical results on 100 independent trials show a success of more than 90% of cases, the proposed IIPO algorithm substantially outperforms other comparative algorithms in terms of accuracy of estimated coefficients, convergence, fitness, output responses, noise analysis, stability, and reliability. 1 1 All source codes are fully and publicly available at https://github.com/ali-ece. [ABSTRACT FROM AUTHOR]