Abstract
This paper presents a hybrid adaptive dynamic programming (hybrid-ADP) approach for determining the optimal continuous and discrete control laws of a switched system online, solely from state observations. The new hybrid-ADP recurrence relationships presented are applicable to model-free control of switched hybrid systems that are possibly nonlinear. The computational complexity and convergence of the hybrid-ADP approach are analyzed, and the method is validated numerically showing that the optimal controller and value function can be learned iteratively online from state observations.
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.
