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Swarm intelligence techniques applied to nonlinear systems state estimation

Nobahari, H ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1007/978-3-642-37880-5_10
  3. Publisher: Springer-Verlag Berlin Heidelberg , 2013
  4. Abstract:
  5. In this chapter, a new class of filters based on swarm intelligence is introduced for nonlinear systems state estimation. As a subset of heuristic filters, swarm filters formulate a nonlinear system state estimation problem as a stochastic dynamic optimization problem and utilize swarm intelligence techniques such as particle swarm optimization and ant colony optimization to find and track the best estimate. As a subset of nonlinear filters, swarm filters can successfully compete with well-known nonlinear filters such as unscented Kalman filter, etc
  6. Keywords:
  8. Source: Advances in Heuristic Signal Processing and Applications ; 2013 , Pages 219-241 ; 9783642378805 (ISBN);364237879X (ISBN); 9783642378799 (ISBN)
  9. URL: http://link.springer.com/chapter/10.1007%2F978-3-642-37880-5_10