2011/03/03 by Andrzej Banaszuk, Banaszuk, Andrzej, Vladimir A. Fonoberov +19
Engineering · Decision Sciences · Computer Science · #Real-time simulation and control systems #Probabilistic and Robust Engineering Design #Robotic Path Planning Algorithms
paper · pdf · doi:10.48550/arxiv.1103.0733
Development of robust dynamical systems and networks such as autonomous\naircraft systems capable of accomplishing complex missions faces challenges due\nto the dynamically evolving uncertainties coming from model uncertainties,\nnecessity to operate in a hostile cluttered urban environment, and the\ndistributed and dynamic nature of the communication and computation resources.\nModel-based robust design is difficult because of the complexity of the hybrid\ndynamic models including continuous vehicle dynamics, the discrete models of\ncomputations and communications, and the size of the problem. We will overview\nrecent advances in methodology and tools to model, analyze, and design robust\nautonomous aerospace systems operating in uncertain environment, with stress on\nefficient uncertainty quantification and robust design using the case studies\nof the mission including model-based target tracking and search, and trajectory\nplanning in uncertain urban environment. To show that the methodology is\ngenerally applicable to uncertain dynamical systems, we will also show examples\nof application of the new methods to efficient uncertainty quantification of\nenergy usage in buildings, and stability assessment of interconnected power\nnetworks.\n