AFOSR Grant FA 9550 - 05 - 1 - 0401 “ Control and Information Architecture for Coordinated Networked Systems ” Principal Investigator :
نویسنده
چکیده
A unifying framework for the design and operation of networked coordinated systems has been researched with developments focusing on application in the management of autonomous vehicles which are subject to large external disturbances, such as wind gusts. The benchmark problem is the use of intervehicle communication and active control to effect collision avoidance in multi-vehicle systems with significant environmental disturbances. The central aim of the work was to combine constrained optimal control, achieved via so-called Model Predictive Control methods, with limited capacity communication link resource assignment to achieve collision avoidance with a nominal fleet formation and a specified level of external disturbances. The core results concern the use of the covariance or quantified uncertainty of the estimate of the other vehicles’ positions as the link between communications resource assignment – more bits of communications means more accurate position estimates – and collision avoidance requirements – close vehicles in the formation require more accurate position information to avoid collision. A computational tool is derived. The work has been presented at AFRL.
منابع مشابه
Specification , Design and Verification of Distributed Embedded Systems Afosr Grant Fa 9550 - 06 - 1 - 0303
We are investigating the specification, design and verification of distributed systems that combine communications, computation and control in dynamic, uncertain and adversarial environments. Our goal is to develop methods and tools for designing control policies, specifying the properties of the resulting distributed embedded system and the physical environment, and proving that the specificat...
متن کاملFinal report on AFOSR FA 9550 - 07 - 1 - 0426 - entitled Novel Mathematical and Computational Techniques for Robust Uncertainty Quantification
متن کامل
Global convergence rate analysis of unconstrained optimization methods based on probabilistic models
We present global convergence rates for a line-search method which is based on random first-order models and directions whose quality is ensured only with certain probability. We show that in terms of the order of the accuracy, the evaluation complexity of such a method is the same as its counterparts that use deterministic accurate models; the use of probabilistic models only increases the com...
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تاریخ انتشار 2010