On-Line Parameters Estimation Using Fast Genetic Algorithm

نویسندگان

  • Ali Hussein Hasan
  • Aleksandr N. Grachev
چکیده

The requirements for on-line identification of system parameters have a critical needing for engineering applications, such as fault diagnosis and process detection. The classical identification methods, such as least-square method, are calculus-based search method. These methods are suffered from many problems, such as a proper initial values of the identified parameters; the objective function requires an exact definition of the gradient or higher-order derivatives; also a possibility to fall into a local minimum. In this paper we develop on-line, robust, efficient, and global optimization method for parameters estimation based on fast genetic algorithms with special reserve elite population. The simulation results show that the proposed algorithm is very fast to find and adapt the estimated parameters. KeywordsParameters Identification; Reserve Elite Population; Fast Genetic Algorithm for Real Time Applications

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تاریخ انتشار 2014