Attractor Selection in Nonlinear Energy Harvesting Using Deep Reinforcement Learning

no code implementations • 3 Oct 2020 • Xue-She Wang, Brian P. Mann

Recent research efforts demonstrate that the intentional use of nonlinearity enhances the capabilities of energy harvesting systems.

reinforcement-learning Reinforcement Learning (RL) +1

A Model-Free Sampling Method for Estimating Basins of Attraction Using Hybrid Active Learning (HAL)

no code implementations • 24 Mar 2020 • Xue-She Wang, Samuel A. Moore, James D. Turner, Brian P. Mann

The proposed method is based upon hybrid active learning (HAL) and is designed to find and label the "informative" samples, which efficiently determine the boundary of BoA.

Active Learning

Constrained Attractor Selection Using Deep Reinforcement Learning

no code implementations • 23 Sep 2019 • Xue-She Wang, James D. Turner, Brian P. Mann

This paper describes an approach for attractor selection (or multi-stability control) in nonlinear dynamical systems with constrained actuation.

reinforcement-learning Reinforcement Learning (RL)