A fuzzy logic controller strategy for battery energy management in a grid connected electro-thermal residential microgrid is presented. The fuzzy control policy manages the power of the microgrid storage elements in order to minimize a set of quality indices involving, among others, the power profile exchanged with the mains. Numerical simulations using real measured data generation and consumption are provided to both validate the control design and to highlight the benefits of including thermal elements in the overall energy management strategy of the system. © 2014 IEEE.Peer ReviewedPostprint (published version

Molecular motors convert chemical energy into mechanical motion and power the transport of material within living cells; the motion of a motor is thought to be influenced by stochastic chemical state transitions of the molecule as well as intramolecular diffusion of one motor head seeking the next binding site. Existing models for the motility of single-headed monomeric motors that map the system to a simplified two-state Brownian ratchet have some predictive power, but in general are unable to elucidate the contributions of different molecular level processes to the overall effective parameters. In this work, we build a detailed molecular level model of monomeric kinesin motility that naturally incorporates conformational changes (power strokes) and biased diffusion. Our results predict that mean velocity is most sensitive to the power stroke size, while run length distribution is sensitive primarily to the strength of the microtubule bias potential with a weak dependence on power stroke that can be tuned by the strength of an applied load. In addition, we demonstrate that motor pairs attached to the same cargo can cooperatively function to increase motility in both the plus- and minus-end directions. These findings illustrate the importance of a detailed mechanochemical model for dissecting the contributions of microscopic parameters to monomeric kinesin dynamics.

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