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. © 2012 Springer-Verlag.
CITATION STYLE
Nobahari, H., & Sharifi, A. (2012). A novel heuristic filter based on ant colony optimization for non-linear systems state estimation. In Communications in Computer and Information Science (Vol. 316 CCIS, pp. 20–29). https://doi.org/10.1007/978-3-642-34289-9_3
Mendeley helps you to discover research relevant for your work.