Abstract
For the linear discrete time-invariant stochastic systems with unknown model parameters and noise variances, substituting their online consistent estimators into the steady-state optimal Riccati equation, a self-tuning Riccati equation is presented. By the dynamic variance error system analysis (DVESA) method, it is proved that the self-tuning Riccati equation converges to the steady-state optimal Riccati equation. The proposed results can be applied to design a new self-tuning information fusion Kalman filter, and to prove its convergence.
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.
