Research on Particle Filter Algorithm Based on Improved Grey Wolf Algorithm

Authors

Weigang Li, Engineering Research Center for Metallurgical Automation and Detecting Technology of Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China;
Li Yang, Engineering Research Center for Metallurgical Automation and Detecting Technology of Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China;
Yuntao Zhao, Engineering Research Center for Metallurgical Automation and Detecting Technology of Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China;
Baokang Yan, Engineering Research Center for Metallurgical Automation and Detecting Technology of Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China;

Abstract

Abstract: The traditional particle filter algorithm is prone to particle depletion and weight degradation, and a large number of particles are needed to make an accurate estimation of non-linear system. A novel particle filter algorithm based on grey wolf optimization algorithm is proposed. The particles are employed to characterize the individuals of grey wolf and simulate the process of wolf hunting, which makes the particles move to the high likelihood region of posterior probability and improve the rationality of the distribution of the particles. Levy flight strategy is introduced in grey wolf algorithm to improve the convergence speed. The adaptive weight adjustment is adopted before partial resampling to increase the diversity of the particles. The results of simulation experiment show that the improved algorithm upgrades the estimation accuracy of particle filter, ensures the diversity of particles and the rationality of particle distribution, and reduces the number of particles required for state estimation.

Recommended Citation

Li, Weigang; Yang, Li; Zhao, Yuntao; and Yan, Baokang (2021) "Research on Particle Filter Algorithm Based on Improved Grey Wolf Algorithm," Journal of System Simulation: Vol. 33: Iss. 1, Article 4.
DOI: 10.16182/j.issn1004731x.joss.19-0276
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss1/4

First Page

37

Revised Date

2019-08-26

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-0276

Last Page

45

CLC

TP391.9

Recommended Citation

Li Weigang, Li Yang, Zhao Yuntao, Yan Baokang. Research on Particle Filter Algorithm Based on Improved Grey Wolf Algorithm[J]. Journal of System Simulation, 2021, 33(1): 37-45.

DOI

10.16182/j.issn1004731x.joss.19-0276