These two papers were written and submitted to the conference AIAA SciTech Forum, which is the world’s largest event for aerospace research and development, while Stefan was finishing his PhD at the University of South Florida. He received the decision that the papers had been accepted after he was employed with us – therefore his affiliation in these papers is with Combine.
The project Stefan was part of during his PhD studies was funded by the Air Force Research Laboratory in USA. His studies were mainly in controls, specifically Event-Triggered Adaptive Control of Multiagent Systems.
One of the papers is on “Scheduling Local Information Exchange in Linear Multiagent Systems Through an Event-Triggering Approach” which is mainly theoretical work. The other paper “Experimental Results of a Quadrotor UAV with a Model Reference Adaptive Controller in the Presence of Unmodeled Dynamics” is focused on experimental work using a quadcopter.
Scheduling Local Information Exchange in Linear Multiagent Systems Through an Event-Triggering Approach?
This paper presents a distributed event-triggered control algorithm for linear time-invariant multiagent systems to schedule local information exchange. The proposed distributed event-triggered control involves a dynamic threshold, which is a function of the error between a dynamical system and its reference model and, in addition, contains an ex-ponentially decaying term to minimize local information exchange during the transient response. This dynamic threshold significantly decreases network utilization (i.e., number of events). Moreover, in contrast to the sampled data exchange approach, which is widely used in the event-triggered control literature, we use a solution-predictor curve exchange method. This method predicts the time trajectories of agents and has the ability to significantly decrease network utilization compared to sampled data exchange. Using graph theory and Lyapunov stability tools, we provide rigorous system-theoretic analysis and show the efficacy of the proposed approach through a numerical example.
Experimental Results of a Quadrotor UAV with a Model Reference Adaptive Controller in the Presence of Unmodeled Dynamics
This paper presents experimental results related to the trajectory tracking performance of a recently developed model reference adaptive control (MRAC) of a quadrotor unmanned aerial vehicle carrying a suspended load under wind turbulance. The suspended load as an unmodeled dynamics and the wind as a constant disturbance significantly degrade the tracking performance of the nominal controller. We compare the performance of the mentioned MRAC with the performances of the nominal controller and the standard MRAC through a series of experiments to elucidate its efficacy in reducing the effects of unmodeled dynamics.