Abstract
In this article has been identified linear stationary roll dynamic model for unmanned air vehicle with the weak exciting input signal and sensor measurements noise using the two-step method, maximum likelihood method and the genetic optimization algorithm. Due to the weak frequency content of the input signal, eigenvalues of the information matrix are close to zero, and the use of the output error method often gives the wrong solutions in each cycle of the identification algorithm based on the Monte Carlo method. Ill-conditioned information matrix in the identification of dynamic model occurs due to linear relationships between variables. The two-step identification method finds the ratio of the parameters in the first stage. In the second step, the identification algorithm is conducted for the vector of parameters with reduced size. The two-stage identification method gives the right solution with the permissible errors for each execution of the identification process
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
