Ensemble Control of Stochastic Oscillators via Periodic and Feedback Control

TL;DR

This paper develops a control strategy for steering the phase distribution of large populations of stochastic oscillators to a desired target distribution using a combination of periodic and feedback control, with theoretical analysis and numerical validation.

Contribution

It introduces a novel ensemble control method that combines periodic and feedback inputs to steer stochastic oscillator populations, including reachability analysis and convergence guarantees.

Findings

The reachability of phase distributions is characterized via Fourier coefficients.

A convex optimization approach is proposed to design periodic controls.

The combined control method accelerates convergence even with measurement errors.

Abstract

We address the problem of steering the phase distribution of oscillators all receiving the same control input to a given target distribution. In a large population limit, the distribution of oscillators can be described by a probability density. Then, our problem can be seen as that of ensemble control with a constraint on the steady-state density. In particular, we consider the case where oscillators are subject to stochastic noise, for which the theoretical understanding is still lacking. First, we characterize the reachability of the phase distribution under periodic feedforward control via the Fourier coefficients of the target density and the phase sensitivity function of oscillators. This enables us to design a periodic input that makes the stationary distribution of oscillators closest to the target by solving a convex optimization problem. Next, we devise an ensemble control method combining periodic and feedback control, where the feedback component is designed to accelerate the convergence of the distribution of oscillators. We exhibit some convergence results for the proposed method, including a result that holds even under measurement errors in the phase distribution. The effectiveness of the proposed method is demonstrated by a numerical example.