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arXiv:2611.15258 · v1

Exact Decisions and Certified Values in $L_\infty$-Norm Computation from State-Space Representations

首次提交 2026-11-11 17:46
版本更新 2026-11-11 17:46
雷达观测 2026-11-13 11:11
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摘要

Computing the L∞L_\infty-norm of a time-invariant linear ordinary differential control system is a routine task in robust control, usually delegated to floating-point routines that perform well on most practical systems. Behind the numerical value, however, lies a discrete decision: whether a pole lies on the imaginary axis, and whether a mode of a realization is actually a pole of the transfer matrix. Floating-point arithmetic can only replace this decision with a tolerance. This paper explains, for a control audience, what reliable symbolic-numeric computation offers for this problem: exact arithmetic where a decision has to be made, and certified enclosures where a value has to be computed. We show how the problem is turned into a small polynomial system directly from state-space data, how this system is solved in practice, and what it costs. A benchmark on the {\tt COMPleib} library and on families of systems with known norms shows that two standard numerical routines err in opposite directions on the imaginary-axis decision, and never on the same system, while the certified method decides it correctly on every instance tested and computes the norm at a cost comparable to that of the numerical routines on most systems. We conclude with practical guidelines for users of numerical tools.

作者备注:6 pages, 1 table. Submitted to the European Control Conference (ECC 2027)

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v1 · 2026-11-11 17:46 · 最新观测版本

Exact Decisions and Certified Values in $L_\infty$-Norm Computation from State-Space Representations

Computing the L∞L_\infty-norm of a time-invariant linear ordinary differential control system is a routine task in robust control, usually delegated to floating-point routines that perform well on most practical systems. Behind the numerical value, however, lies a discrete decision: whether a pole lies on the imaginary axis, and whether a mode of a realization is actually a pole of the transfer matrix. Floating-point arithmetic can only replace this decision with a tolerance. This paper explains, for a control audience, what reliable symbolic-numeric computation offers for this problem: exact arithmetic where a decision has to be made, and certified enclosures where a value has to be computed. We show how the problem is turned into a small polynomial system directly from state-space data, how this system is solved in practice, and what it costs. A benchmark on the {\tt COMPleib} library and on families of systems with known norms shows that two standard numerical routines err in opposite directions on the imaginary-axis decision, and never on the same system, while the certified method decides it correctly on every instance tested and computes the norm at a cost comparable to that of the numerical routines on most systems. We conclude with practical guidelines for users of numerical tools.

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