Abstract: Methods and systems for information exchange of a vehicle in a networked multiagent system are disclosed. The methods and systems include: receiving a last neighbor dataset broadcasted by a neighbor vehicle; determining a current dataset based on the last neighbor dataset and a last vehicle dataset of the first vehicle; identifying a violation of an event-triggering condition by comparing a difference between the last vehicle dataset and the current dataset with a dynamic threshold; determining a transmission dataset being associated with the current dataset; and in response to the violation, broadcasting the transmission dataset to the neighbor vehicle. The dynamic threshold is defined by an exponentially decaying term and an error between a vehicle state of the first vehicle and a reference state. Other aspects, embodiments, and features are also claimed and described.

Abstract: Methods and systems for information exchange of a vehicle in a multiagent system are disclosed. The methods and systems include: receiving one or more neighboring states broadcast by one or more neighboring vehicles; transmitting a last broadcast state of the vehicle to the one or more neighboring vehicles; determining a current state of the vehicle based on the one or more neighboring states and the last broadcast state; determining a norm-free information exchange triggering condition based on the last broadcast state, the current state, and an estimated command; and in response to the current state violating the norm-free information exchange triggering condition, transmitting the current state to the one or more neighboring vehicles. Other aspects, embodiments, and features are also claimed and described.

Abstract: Various examples are provided related to adaptive architectures for controlling uncertain system with unmodeled dynamics. A closed-loop dynamical system subject to an adaptive controller can remain stable if there does not exist significant unmodeled dynamics or the effect of system uncertainties is negligible. In one example, a system includes a controller that can receive one or more input signals including control signals, sensor data associated with operation of the aircraft or aviation system, or a combination thereof; generate an system control signal utilizing a model reference adaptive control architecture comprising an adaptive robustifying term that maintains system stability within defined bounds; and provide the system control signal to an actuator or other system components to adjust operation of, e.g., an aircraft or aviation system.

Abstract: The present disclosure describes an actuator system comprising an actuator unit that is configured to be positioned next to a structure; and an adaptive controller unit that is configured to receive a command input for the actuator unit and output an actuator command based on a reference model of a physical system that includes the actuator unit and the structure, wherein the actuator command does not alter trajectories of the reference model. In various embodiments, the uncertain dynamical system of the physical system is augmented with the actuator dynamics to provide improved stability.