Abstract
Abstract The paper presents new methods for nonlinear filtering, nonlinear parameter estimation and nonlinear prediction through a new concept named “intersample linearization”. The nonlinear filtering and parameter estimation methods shown in the paper are based on the algorithm of nonlinear prediction, which applies multi intersample linearization and approximates the nonlinear state evolution in increments computed with linear equations. Through multi-step ahead prediction, nonlinear model predictive control problems and optimum stochastic tracking problems may be solved.
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.
