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Optimal Control of an Electromechanical Energy Harvester
Dario Lucente1, Alessandro Manacorda2, Andrea Plati3
1Department of Mathematics & Physics, University of Campania "Luigi Vanvitelli", Viale Lincoln 5, 81100 Caserta, Italy.
Entropy (Basel, Switzerland)
|March 28, 2025
Summary
Researchers optimized stochastic control protocols for energy harvesters by adjusting electrical resistance over time. Dynamic control strategies outperform constant resistance, maximizing average power extraction from mechanical vibrations.
Area of Science:
- Applies control theory to stochastic systems
- Focuses on optimal control protocols for energy harvesting
Background:
- Deterministic control theory techniques are increasingly used for stochastic processes.
- Optimal control aims to maximize reward functions while managing system states under environmental fluctuations.
Purpose of the Study:
- To investigate optimal control strategies for stochastic systems, using an energy harvester model.
- To determine if time-varying control parameters can improve performance over constant parameters.
Main Methods:
- Applied control theory tools to a stochastic energy harvester model.
- Analyzed optimal control in a perturbative regime near the stationary state.
- Investigated the impact of time-varying electrical resistance on power extraction.
Main Results:
- Developed optimal control protocols for a class of stochastic systems.
- Demonstrated that time-varying resistance protocols yield superior average power extraction compared to constant resistance.
- Showcased improved performance over static control solutions.
Conclusions:
- Optimal control strategies can significantly enhance energy harvesting efficiency.
- Dynamic adjustment of system parameters, like electrical resistance, is key to maximizing power output in stochastic environments.
- The study provides a framework for designing advanced control protocols for stochastic energy harvesters.
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