Abstract
Abstract We propose a highly parallelizable Newton-type method for nonlinear model predictive control by exploiting the particular structure of the associated Karush-Kuhn-Tucker conditions. These equations are approximately decoupled into single step subproblems along the prediction horizon for parallelization. The coupling variable of each subproblem is approximated toward its optimal value by a simple but effective method in every iteration. The proposed algorithm is applied to control a quadrotor. The numerical simulation results show that the proposed algorithm is highly parallelizable and converges with only a few iterations even to a high accuracy. The proposed method is also shown to be faster compared with several state-of-the-art algorithms.
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.
