Expensive control of long-time averages using sum of squares and its application to a laminar wake flow
Deqing Huang, Bo Jin, Davide Lasagna, Sergei Chernyshenko, and Owen, Tutty

TL;DR
This paper introduces a sum-of-squares based convex optimization method for designing cost-effective nonlinear controllers targeting long-time average costs, demonstrated on laminar wake flow control.
Contribution
It develops a convex optimization approach for long-time average cost control using sum-of-squares techniques, resolving non-convexity issues in controller design.
Findings
Effective control of vortex shedding in wake flow
Validated approach on reduced-order and direct numerical simulations
Achieved control with small, cost-effective actuation
Abstract
The paper presents a nonlinear state-feedback control design approach for long-time average cost control, where the control effort is assumed to be expensive. The approach is based on sum-of-squares and semi-definite programming techniques. It is applicable to dynamical systems whose right-hand side is a polynomial function in the state variables and the controls. The key idea, first described but not implemented in (Chernyshenko et al., Phil. Trans. R. Soc. A, 372, 2014), is that the difficult problem of optimizing a cost function involving long-time averages is replaced by an optimization of the upper bound of the same average. As such, controller design requires the simultaneous optimization of both the control law and a tunable function, similar to a Lyapunov function. The present paper introduces a method resolving the well-known inherent non-convexity of this kind of optimization.…
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Taxonomy
TopicsModel Reduction and Neural Networks · Computational Fluid Dynamics and Aerodynamics · Fluid Dynamics and Turbulent Flows
