Abstract
With regards of the asynchronous clock and stratification effect in cyber-channels as well as the model disturbances in physical channels, a joint localization and tracking problem is studied in this chapter. In particular, an integrated state and clock model is constructed at the beginning. Then, an asynchronous localization algorithm is designed to locate the position of AUV. With the estimated position information, we develop a reinforcement learning-based tracking controller for AUV to track the reference point. Especially, the multivariate probabilistic collocation method (M-PCM) is employed to evaluate the model uncertainty. Besides, the performance analysis of the proposed algorithm is also presented. Finally, simulation results are given to reveal the effectiveness of the proposed algorithm.
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.
