Optimization with affine homogeneous quadratic integral inequality constraints

Fantuzzi G, Wynn A, Goulart PJ, Papachristodoulou A (2017)


Publication Type: Journal article

Publication year: 2017

Journal

Book Volume: 62

Pages Range: 6221-6236

Journal Issue: 12

DOI: 10.1109/TAC.2017.2703927

Abstract

We introduce a new technique to optimize a linear cost function subject to an affine homogeneous quadratic integral inequality, i.e., the requirement that a homogeneous quadratic integral functional affine in the optimization variables is nonnegative over a space of functions defined by homogeneous boundary conditions. Such problems arise in control and stability or input-to-state/output analysis of systems governed by partial differential equations (PDEs), particularly fluid dynamical systems. We derive outer approximations for the feasible set of a homogeneous quadratic integral inequality in terms of linear matrix inequalities (LMIs), and show that a convergent sequence of lower bounds for the optimal cost can be computed with a sequence of semidefinite programs (SDPs). We also obtain inner approximations in terms of LMIs and sum-of-squares constraints, so upper bounds for the optimal cost and strictly feasible points for the integral inequality can be computed with SDPs. We present QUINOPT, an open-source add-on to YALMIP to aid the formulation and solution of our SDPs, and demonstrate our techniques on problems arising from the stability analysis of PDEs.

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APA:

Fantuzzi, G., Wynn, A., Goulart, P.J., & Papachristodoulou, A. (2017). Optimization with affine homogeneous quadratic integral inequality constraints. IEEETransactions on Automatic Control, 62(12), 6221-6236. https://dx.doi.org/10.1109/TAC.2017.2703927

MLA:

Fantuzzi, Giovanni, et al. "Optimization with affine homogeneous quadratic integral inequality constraints." IEEETransactions on Automatic Control 62.12 (2017): 6221-6236.

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