An Iterative Approach to Optimal Control Design for Oscillator Networks

We propose a computational framework for optimal control design of oscillator networks. We first introduce a new system representation to eliminate challenges arising from the periodic nature of oscillators. The representation allows us to consider the general problem of pattern formation for oscillators as a classical point-to-point steering. We then develop a novel control design technique that offers the flexibility to blend the time-optimal and energy-optimal considerations with a parameter of choice. We demonstrate the applicability of the proposed framework to a variety of neuroscience applications.