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Circuits, Systems, and Signal Processing

, Volume 37, Issue 8, pp 3558–3575 | Cite as

Joint Parameter and State Estimation Based on Marginal Particle Filter and Particle Swarm Optimization

  • Ramazan Havangi
Article
  • 97 Downloads

Abstract

In this paper, a method for the dual estimation is proposed. This approach combines extended marginal particle filter (EMPF) with particle swarm optimization (PSO) for simultaneous estimation of state and parameter values in nonlinear stochastic state–space models. In the proposed method, the states are estimated by EMPF and the parameters are estimated by PSO. The performance of proposed algorithm is evaluated in two examples. Simulation results demonstrate the feasibility and efficiency of the proposed method.

Keywords

Extended marginal particle filter Particle filter PSO Dual estimation 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Faculty of Electrical and Computer EngineeringUniversity of BirjandBirjandIran

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