TY - GEN
T1 - An Iterative Approach to Optimal Control Design for Oscillator Networks
AU - Singhal, Bharat
AU - Vu, Minh
AU - Zeng, Shen
AU - Li, Jr Shin
N1 - Publisher Copyright:
© 2023 American Automatic Control Council.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85167798630&partnerID=8YFLogxK
U2 - 10.23919/ACC55779.2023.10156503
DO - 10.23919/ACC55779.2023.10156503
M3 - Conference contribution
AN - SCOPUS:85167798630
T3 - Proceedings of the American Control Conference
SP - 3466
EP - 3471
BT - 2023 American Control Conference, ACC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 American Control Conference, ACC 2023
Y2 - 31 May 2023 through 2 June 2023
ER -