Title :
On statistical sampling for system testing
Author :
Duncan, T.E. ; Mandl, P. ; Pasik-Duncan, B.
Author_Institution :
Dept. of Math., Kansas Univ., Lawrence, KS, USA
fDate :
1/1/1994 12:00:00 AM
Abstract :
In this note, the theory of locally asymptotically normal experiments is used to test hypotheses about the parameters of a controlled, linear stochastic system. The tests are formulated for both continuous and sampled observations of the input and the output. For the sampled observations, a constant bias property for a quadratic variation estimate of the local variance parameters of the noise is verified. A numerical example is given using the methods
Keywords :
control system synthesis; linear systems; parameter estimation; statistical analysis; stochastic systems; constant bias property; continuous observations; controlled linear stochastic system; hypothesis testing; local variance parameters; locally asymptotically normal experiments; sampled observations; statistical sampling; system testing; Control systems; Gaussian distribution; Linear systems; Mathematics; Probability; Random variables; Sampling methods; Statistics; Stochastic systems; System testing;
Journal_Title :
Automatic Control, IEEE Transactions on
