Tags:controller synthesis, maneuver automata, model predictive control, reach-avoid problems and reachability analysis
Abstract:
We present a MATLAB toolbox for Automated Reachset Optimal Control (AROC) that automatically synthesizes verified controllers for solving reach-avoid problems using reachability analysis. The toolbox implements two different types of control approaches: In model predictive control a feasible controller is constructed and verified on-the-fly during online application of the system. For motion-primitive-based control, on the other hand, controllers for many motion primitives are synthesized offline and then used for online motion planning with a maneuver automaton. Since our toolbox considers general nonlinear systems with input constraints, state constraints, and bounded disturbances, it is applicable to a very broad class of systems as we demonstrate with several numerical examples.
AROC: a Toolbox for Automated Reachset Optimal Controller Synthesis