2016/09/12 by Arnab Saha, Saha, Arnab, Rahul Marathe +3
Computer Science · Engineering · #Advanced Control Systems Optimization #FOS: Physical sciences #Iterative Learning Control Systems #Neural Networks and Applications #Statistical Mechanics (cond-mat.stat-mech)
paper · pdf · doi:10.48550/arxiv.1609.03459
openalex publication_date 2016/09/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Thermodynamics of nanoscale devices is an active area of research. Despite their noisy surround- ing they often produce mechanical work (e.g. micro-heat engines) or display rectified Brownian motion (e.g. molecular motors). This invokes the research in terms of experimentally quantifiable thermodynamic efficiencies. To enhance the efficiency of such devices, close-loop control is an useful technique. Here a single Brownian particle is driven by a harmonic confinement with time-periodic contraction and expansion, together with a velocity feedback that acts on the particle only when the trap contracts. Due to this feedback we are able to extract thermodynamic work out of the system having single heat bath without violating the Second Law of Thermodynamics. We analyse the system using stochastic thermodynamics.