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Event Details

  • Tuesday, November 7, 2017
  • 11:30 - 12:00

Integrated Actuation, Sensing and Sampling in Autonomous and Networked Systems

A wide range of current and emerging engineering applications address the development of novel autonomous systems with agile maneuvering and robust perception in dynamic, complex and unpredictable environments well beyond what is currently feasible in practice. Further, systems with a rich array of sensors but limited power and/or processing resources have more potential information available than they can use and are forced to subsample the data. In the work presented here, integration of the tasks of modeling, control, sensing and sensor selection for autonomous systems is considered. The lack of a separation principle between control and estimation in nonlinear systems is leveraged for improved system observability based on the idea of co-design of control and estimation. We build on observability analysis for general nonlinear systems to provide a basis for a framework to investigate dynamic sensor selection to optimize a measure of observability, specifically the condition number of an observability Gramian. These ideas will be discussed relative to both engineering applications in the form of motion planning for range and bearing only navigation in autonomous vehicles, vortex position and strength estimation from pressure measurements on airfoils, and effective strain sensor placement on insect wings for inertial measurements.