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Optimal Discrete-Time Energy Harvesting From Infinite-Dimensional Stochastic Systems

[+] Author Affiliations
J. T. Scruggs

University of Michigan, Ann Arbor, MI

I. L. Cassidy

Lord Corporation, Cary, NC

Paper No. DSCC2014-6185, pp. V002T32A002; 10 pages
  • ASME 2014 Dynamic Systems and Control Conference
  • Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing
  • San Antonio, Texas, USA, October 22–24, 2014
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4619-3
  • Copyright © 2014 by ASME


This paper considers the optimization of discrete-time control systems for power generation from stochastically-excited linear dynamical systems, characterized by infinite-dimensional dynamics. Weiner-Hopf theory is used to determine the physical upper bound on stationary power generation. The resultant expressions for power generation do not require a finite-dimensional state-space model to be specified at any point in the analysis. However, the constraint that the controller be causal leads to the need to perform spectral factorizations on two associated power spectra. In many cases, analytical solutions to these factorizations are intractable, and approximate numerical techniques must be used. This paper makes use of subspace identification techniques for approximate spectral factorization. The concepts are illustrated in a wave energy conversion example.

Copyright © 2014 by ASME



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