Abstract
Iterative Feedback Tuning (IFT) is a direct tuning method using closed loop experimental data. The method is based on numerical optimization and in each iteration an unbiased gradient estimate is used. In this contribution we show how to use IFT to do robust loopshaping. One method, based on the approach suggested by Glover and McFarlane [1], uses an approximate H ∞ cost function and alternates between updating the loop gains and the robustness margins. In a second, H 2 based method, a joint criterion of robustness and performance is optimized. The methods are illustrated on numerical examples.
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.
