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Control Seminar

Vibration Energy Harvesting: An Optimal Control Perspective

Jeff ScruggsAssistant Professor University of Michigan - Department of Civil & Environmental Engineering
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Vibration energy harvesters are electromechanical transducers that capture ambient mechanical vibratory energy and deliver it to an electrical power bus. One application of this idea is the use of piezoelectric transduction to scavenge vibratory energy from structures, for the purpose of powering wireless sensors. Another is the use of floating buoys to harvest energy from ocean waves, as a renewable power source. In many applications, vibrations are stochastic, and available energy is spread across a wide band of frequencies. In such cases, optimal control theory can be used to determine fundamental causal limits on power generation as a function of parameters of the disturbance spectrum and transducer hardware, and can be used to synthesize optimal feedback laws. In this talk, we will examine the manner in which such problems can be posed mathematically, for multi-transducer energy harvesting systems. We also examine the influence of energy flow constraints and losses in the electronics, on the optimal feedback design. Throughout the talk, the theory will be illustrated in the context of both piezoelectric energy scavengers and ocean wave energy systems. In both these examples, it turns out that the flow of energy in these systems, when optimized, can exhibit surprising and counterintuitive behavior.
Jeff Scruggs is an Assistant Professor with the Department of Civil & Environmental Engineering at the University of Michigan, which he joined in September of 2011. He received his B.S. and M.S. degrees in Electrical Engineering from Virginia Tech in 1997 and 1999, respectively, and his Ph.D. in Applied Mechanics from Caltech in 2004. Prior to joining UM, he held postdoctoral positions at Caltech and UCSD, and was on the faculty at Duke University from 2007-11. Scruggs's current research is in the areas of mechanics, vibration, energy, and control. His research is supported by NSF, ONR, and DOE.

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