@article{pecker2025hybrid,

title = {Hybrid resource allocation control in cyber-physical systems: a novel simulation-driven methodology with applications to UAVs},

author = {Ezequiel Pecker-Marcosig and Juan I. Giribet and Rodrigo Castro},

url = {https://doi.org/10.1177/00375497241313404},

doi = {10.1177/00375497241313404},

year  = {2025},

date = {2025-01-01},

journal = {SIMULATION},

volume = {101},

number = {5},

pages = {597–619},

abstract = {Designing hybrid controllers for cyber-physical systems (CPSs) where computational and physical components influence each other is a challenging task, as it requires considering the performance of very different types of dynamics simultaneously. Meanwhile, controlling each of these dynamics separately can lead to unacceptable results. Common approaches to controller design rely on the use of analytical methods. Although this approach can provide formal guarantees of stability and performance, the analytical design of hybrid controllers can become quite cumbersome. Alternatively, modeling and simulation (M&S)-based design techniques have proven successful for hybrid controllers, providing robust results based on Monte Carlo techniques. This requires simulation models and platforms capable of seamlessly composing the underlying hybrid domains. Unmanned Aerial Vehicles (UAVs) are CPSs with sensitive physical–computational couplings. We address the development of a hybrid model and simulation platform for a data collection application involving UAVs with onboard data processing. The quality of control (QoC) of the physical dynamics must be ensured together with the quality of service (QoS) of the onboard software competing for scarce processing resources. In this scenario, it is imperative to find safe trade-offs between flight stability and processing throughput that can adapt to uncertain environments. The goal is to design a hybrid supervisory controller that dynamically adapts the use of resources to balance the performance of both aspects in a CPS, while ensuring system-level QoS. We present the end-to-end M&S-based design methodology, which can be regarded as a design template for a broader class of CPSs.},

keywords = {Cyber-Physical Systems, DEVS, QSS, UAVs},

pubstate = {published},

tppubtype = {article}

}

@article{pecker-marcosig_correct_2023,

title = {Correct and efficient UAV missions based on temporal planning and in-flight hybrid simulations},

author = {Ezequiel Pecker-Marcosig and Sebastián Zudaire and Rodrigo Castro and Sebastián Uchitel},

url = {https://www.sciencedirect.com/science/article/pii/S092188902300043X},

doi = {10.1016/j.robot.2023.104404},

issn = {09218890},

year  = {2023},

date = {2023-01-01},

journal = {Robotics and Autonomous Systems},

volume = {164},

pages = {104404},

abstract = {Controller synthesis has been successfully applied in UAV applications, to construct a mission plan that is guaranteed to be correct with respect to a user-provided specification. Albeit being correct, these plans may not be optimal in the vehicle's trajectory, battery consumption, or other criteria which the user may consider relevant. A possibility would be to apply a quantitative synthesis approach where the target is to compute efficient plans before the mission, at a higher cost of complexity and potential limitations in the optimization goals to achieve. As an alternative, in this paper we propose doing the plan optimization in-flight. For this, we use available tools that synthesize controllers with multiple controllable choices and later select among these choices in-flight using hybrid simulations ranking them according to the optimization objective. We present the advantages of our approach and validate them using software-in-the-loop simulation with typical UAV mission scenarios.},

note = {Publisher: North-Holland},

keywords = {Controller synthesis, Cyber-Physical Systems, DEVS, Hybrid simulation, LTL},

pubstate = {published},

tppubtype = {article}

}