Abstract
Based on general Ackermann’s formula, the MIMO system’s pole configuration design has free parameters that can be adjusted to optimize the system performance. We proposed an improved grey wolf algorithm with adaptive spiral search, proportional weight encirclement, and intergenerational competition mechanism to adjust free parameters to solve this problem. Aiming at the shortcomings that traditional grey wolf optimization algorithm isn’t stable and the convergence accuracy is low later. First, the spiral search mode is introduced to improve the algorithm’s ability by increasing the search trajectory of the wolf pack. The later stage of the algorithm is gradually switched to the proportionally weighted encirclement to achieve an accurate local search. Besides, an intergenerational competition mechanism is introduced to ensure the wolf pack’s leadership ability to improve convergence accuracy and algorithm stability. The algorithm is then benchmarked on 12 well-known benchmark functions. Its stableness and accuracy are verified compared to basic grey wolf optimizer, PSO, whale optimization algorithm, and firefly algorithm. Numerical experiments show that the improved grey wolf algorithm has advantageous searchability and fast convergence. Based on the improved algorithm, the pole configuration design of the MIMO system of the generalized Ackermann’s formula has better output performance.
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Acknowledgement
This work was partially supported by the Minjiang University under Grant MJY192026, 103952020001, 2019MHX100, MJIS2020D003, 2019L3009 and JAT200444.
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Zhang, X.Q., Wu, C.Y., Jang, L.Y., Shi, L., Guo, J.R. (2021). Pole-Placement Control of Hypothetical Loop Decoupling Design Based on Improved Grey Wolf Optimization Algorithm. In: Hassanien, A.E., et al. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). AICV 2021. Advances in Intelligent Systems and Computing, vol 1377. Springer, Cham. https://doi.org/10.1007/978-3-030-76346-6_24
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DOI: https://doi.org/10.1007/978-3-030-76346-6_24
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