Genetic adaptive state estimation

@inproceedings{Gremling2000GeneticAS,
  title={Genetic adaptive state estimation},
  author={James R. Gremling and Kevin M. Passino},
  year={2000}
}
A genetic algorithm (GA) uses the principles of evolution, natural selection, and genetics to offer a method for parallel search of complex spaces. This paper describes a GA that can perform on-line adaptive state estimation for linear and nonlinear systems. First, it shows how to construct a genetic adaptive state estimator where a GA evolves the model in a state estimator in real time so that the state estimation error is driven to zero. Next, several examples are used to illustrate the… CONTINUE READING
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