Active parametric identification of stochastic nonlinear continuous-discrete systems based on time domain linearization
Keywords:
parameter estimation, maximum likelihood method, optimal input signal design, fisher information matrix, optimality criterionAbstract
Some theoretical and applied aspects of the active parametric identification of the stochastic nonlinear continuous-discrete systems are discussed for the first time. The original results are obtained for the case when the parameters of mathematical models to be estimated appear in the state and control equations, as well as the initial condition and the covariance matrices of the dynamic noise and measurement errors. An example of optimal parameter estimation for one model structure is shown.
Published
2010-12-17
How to Cite
Chubich, V. (2010). Active parametric identification of stochastic nonlinear continuous-discrete systems based on time domain linearization. Information and Control Systems, (6), 54-61. Retrieved from http://proceedings.spiiras.nw.ru/index.php/ius/article/view/14280
Issue
Section
Stochastic dynamics and chaos