Resolvent-based tools for optimal estimation and control via the Wiener-Hopf formalism
Eduardo Martini, Junoh Jung, Andr\'e V. G. Cavalieri, Peter Jordan,, Aaron Towne

TL;DR
This paper introduces a resolvent-based control method using Wiener-Hopf formalism that enables optimal estimation and control directly from full-rank systems, handling complex disturbances efficiently and with broad applicability.
Contribution
It develops a novel resolvent-based control approach with causality via Wiener-Hopf, applicable to complex flows and high-rank disturbances, overcoming limitations of existing methods.
Findings
Validated on linearized Ginzburg-Landau equation
Analyzed sensor/actuator placement for flow over backward-facing step
Demonstrated control of high-rank flow receptivity
Abstract
The application of control tools to complex flows frequently requires approximations, such as reduced-order models and/or simplified forcing assumptions, where these may be considered low-rank or defined in terms of simplified statistics (e.g. white noise). In this work, we propose a resolvent-based control methodology with causality imposed via a Wiener-Hopf formalism. Linear optimal causal estimation and control laws are obtained directly from full-rank, globally stable systems with arbitrary disturbance statistics, circumventing many drawbacks of alternative methods. We use efficient, matrix-free methods to construct the matrix Wiener-Hopf problem, and we implement a tailored method to solve the problem numerically. The approach naturally handles forcing terms with space-time colour; it allows inexpensive parametric investigation of sensor/actuator placement in scenarios where…
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