Fast and Guaranteed Safe Controller Synthesis for Aerial Vehicle Models

TitleFast and Guaranteed Safe Controller Synthesis for Aerial Vehicle Models
Publication TypeConference Paper
Year of Publication2021
AuthorsFan C, Miller K, Mitra S
Conference NameAIAA Scitech 2021 Forum

We address the problem of synthesizing a controller for nonlinear aerial vehicle models with reach-avoid requirements. Our controller consists of a reference controller and a tracking controller which drives the actual trajectory to follow the reference trajectory or waypoints. We employ a machine learning-based framework to learn a tracking controller that can track any reference trajectory and simultaneously learn a tracking certificate such that the tracking error between the actual trajectory of the closed-loop system and the reference trajectory can be bounded. Moreover, such a bound on the tracking error is independent of the reference trajectory. Using such bounds on the tracking error, we propose a method that can find a reference trajectory by solving a satisfiability problem over linear constraints. Our overall algorithm guarantees that the resulting controller can make sure every trajectory from the initial set of the aerial vehicle satisfies the given reach-avoid requirement.