LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Parameter preference for the continuous super-twisting-like algorithm based on H∞ norm analysis

Photo by efekurnaz from unsplash

In variable structured systems, plenty of designs are built to be homogeneous. Such unperturbed homogeneous dynamics with negative homogeneous degree guarantee finite time convergence. Previous studies provide lower bounds for… Click to show full abstract

In variable structured systems, plenty of designs are built to be homogeneous. Such unperturbed homogeneous dynamics with negative homogeneous degree guarantee finite time convergence. Previous studies provide lower bounds for parameters that result in such finite-time convergence property. In this paper, we propose a new perspective on parameter preference, based on H∞ norm analysis. Contrary to other studies, which propose such norm non-homogeneous or homogeneous, yet of non-zero degree, we build a homogeneous H∞ norm of homogeneous degree zero, thus global and constant. Based on data collected of this norm on the continuous super-twisting-like algorithm, we give recommendations for choosing the parameters.

Keywords: twisting like; parameter preference; continuous super; norm analysis; super twisting; based norm

Journal Title: IFAC-PapersOnLine
Year Published: 2020

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.