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A novel heuristic filter based on ant colony optimization for non-linear systems state estimation

Nobahari, H ; Sharif University of Technology | 2012

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  1. Type of Document: Article
  2. DOI: 10.1007/978-3-642-34289-9_3
  3. Publisher: 2012
  4. Abstract:
  5. A new heuristic filter, called Continuous Ant Colony Filter, is proposed for non-linear systems state estimation. The new filter formulates the states estimation problem as a stochastic dynamic optimization problem and utilizes a colony of ants to find and track the best estimation. The ants search the state space dynamically in a similar scheme to the optimization algorithm, known as Continuous Ant Colony System. The performance of the new filter is evaluated for a nonlinear benchmark and the results are compared with those of Extended Kalman Filter and Particle Filter, showing improvements in terms of estimation accuracy
  6. Keywords:
  7. Ant colonies ; Ant Colony Optimization (ACO) ; Ant colony systems ; Estimation problem ; Filter-based ; Nonlinear benchmark ; Optimization algorithms ; Particle filter ; State space ; Stochastic dynamics ; Heuristic filters ; Non-linear systems state estimations ; Algorithms ; Benchmarking ; Estimation ; Intelligent systems ; Monte Carlo methods ; Nonlinear systems ; State estimation
  8. Source: Communications in Computer and Information Science, 27 October 2012 through 28 October 2012 ; Volume 316 CCIS , October , 2012 , Pages 20-29 ; 18650929 (ISSN) ; 9783642342882 (ISBN)
  9. URL: http://link.springer.com/chapter/10.1007%2F978-3-642-34289-9_3