Optimal control strategies for efficient energy harvesting from ambient vibrations

TL;DR

This paper proposes an optimal control framework for vibratory energy harvesters to improve energy extraction efficiency, addressing theoretical challenges and demonstrating solutions in linear systems under noise.

Contribution

It introduces a novel optimal control formulation for energy harvesting, distinct from LQG, and provides solutions for linear systems with Gaussian noise.

Findings

Optimal control can significantly enhance energy harvesting efficiency.

The formulated problem has non-trivial solutions in time and frequency domains.

The approach addresses theoretical challenges in control for energy harvesting.

Abstract

Ease of miniaturization and minimal maintenance are among the advantages for replacing conventional batteries with vibratory energy harvesters in a wide of range of disciplines and applications, from wireless communication sensors to medical implants. However, the current harvesters do not extract energy from the ambient vibrations in a very efficient and robust fashion, and hence, there need to be more optimal harvesting approaches. In this paper, we introduce a generic architecture for vibration energy harvesting and delineate the key challenges in the field. Then, we formulate an optimal control problem to maximize the harvested energy. Though possessing similar structure to that of the standard LQG problem, this optimal control problem is inherently different from the LQG problem and poses theoretical challenges to control community. As the first step, we simplify it to a tractable problem of optimizing control gains for a linear system subjected to Gaussian white noise excitation, and show that this optimal problem has non-trivial optimal solutions in both time and frequency domains.