Abstract
This paper presents a stabilizing Model Predictive Control (MPC) algorithm based on the off-line computation of a sequence of 1-step controllable sets and a condition that enables flexible, non-monotone convergence towards a suitably chosen terminal set. Such an off-line computed sequence of sets leads to a large region where the MPC algorithm is feasible, regardless of the length of the prediction horizon, while the non-monotone convergence condition is used to improve performance. Both stability and recursive feasibility are guaranteed by construction. The benefits of such an approach are shown in illustrative examples.
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.
