Abstract
By combining strong tracking filter theory with state fusion estimation algorithm, we put forward a new algorithm of state fusion estimation for a class of nonlinear dynamic systems with all sensors having different sampling rates on the basis of distributed information. The algorithm is also extended to the joint state and parameter estimation of a class of nonlinear systems having time-varying parameters with unknown changing law. The effectiveness of the proposed algorithm is illustrated by computer simulations, which show that the new algorithm has strong robustness against model/plant mismatches.
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.
