Proactive planning for persistent missions using composite model-reference adaptive control and approximate dynamic programming

This paper extends prior work on the persistent mission problem where real-time changes in agent capability are included in the problem formulation. Here, we couple the mission planner with a low-level adaptive controller in real time to: (1) Provide robustness against actuator degradations and (2) Use parameters internal to the adaptive controller to provide valuable insight into the physical capabilities of the agent. These parameters, in conjunction with sensor health information, form a more complete measure of agent capability, which is used online and in forward planning to enable both reactive and proactive behavior. Flight results are presented for a persistent mission scenario where actuator degradations are induced to demonstrate: (1) The robustness of the composite adaptive controller and its successful integration with the agent level health-monitoring and mission-level planning systems and (2) The reactive and proactive qualities of the planning system in persistently re-tasking agents under actuator and sensor health degradations.