Abstract
We consider the problem of designing feedback control laws when a complete set of state variables is not available. For linear autonomous systems with quadratic performance criterion, the design problem consists of choosing an appropriate matrix of feedback gains according to a certain objective function. In the literature, the performance of quasi-Newton methods has been reported to be substandard. We try to explain some of these observations and to propose structured quasi-Newton updates. These methods, which take into account the special structure of the problem, show considerable improvement in the convergence. Using test examples from optimal output feedback design, we also can verify these results numerically.
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.
