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A heuristic filter based on firefly algorithm for nonlinear state estimation

Nobahari, H ; Sharif University of Technology | 2017

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  1. Type of Document: Article
  2. DOI: 10.1109/SSCI.2016.7850275
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2017
  4. Abstract:
  5. A new heuristic filter, called firefly filter, is proposed for state estimation of nonlinear stochastic systems. The new filter formulates the state estimation problem as a stochastic dynamic optimization and utilizes the firefly optimization algorithm to find and track the best estimation. The fireflies search the state space dynamically and are attracted to one other based on the perceived brightness. The performance of the proposed filter is evaluated for a set of benchmarks and the results are compared with the well-known filters like extended Kalman filter and particle filter, showing improvements in terms of estimation accuracy. © 2016 IEEE
  6. Keywords:
  7. Firefly algorithm ; Heuristic filter ; Nonlinear stochastic system ; Artificial intelligence ; Bandpass filters ; Benchmarking ; Bioluminescence ; Fire protection ; Nonlinear analysis ; State estimation ; Stochastic systems ; Estimation problem ; Firefly algorithms ; Heuristic filters ; Non-linear stochastic systems ; Nonlinear state estimation ; Optimization algorithms ; Particle filter ; Stochastic dynamics ; Optimization
  8. Source: 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016, 6 December 2016 through 9 December 2016 ; 2017 ; 9781509042401 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/7850275