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A Complete Inverse Optimality Study for a Tank-Liquid System

Optimization and Control · Submitted 26 May 2024

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim We show that the proposed family of stabilizing feedback laws is optimal for a certain meaningful quadratic cost functional.

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arXiv ID2405.16535 (version 1)
Pith IDBXKG6AB6, Pith's permanent record of this paper and its review
CitationFilippos Vokos, Iasson Karafyllis, Miroslav Krstic. "A Complete Inverse Optimality Study for a Tank-Liquid System." arXiv:2405.16535 (2024). https://pith.science/paper/BXKG6AB6
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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,645 input tokens.

What the abstract itself states, as probabilities: claims first 0.08 · states limitation 0.20 · human participants 0.01 · controlled comparison 0.04 · randomized assignment 0.01 · states quantitative result 0.07 · compares with prior results 0.40 · mentions code or data availability 0.02.

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arXiv listing abstract v1. Results and the main claim are underlined; .

This paper presents a complete inverse optimality study for a linearized tank-liquid system where the liquid is described by the viscous Saint-Venant model with surface tension and possible wall friction. We define an appropriate weak solution notion for which we establish existence/uniqueness results with inputs that do not necessarily satisfy any compatibility condition as well as stabilization results with feedback laws that are constructed with the help of a Control Lyapunov Functional. We show that the proposed family of stabilizing feedback laws is optimal for a certain meaningful quadratic cost functional. Finally, we show that the optimal feedback law guarantees additional stronger stability estimates which are similar to those obtained in the case of classical solutions.

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What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 This paper presents a complete inverse optimality study for a linearized tank-liquid system where the liquid is described by the viscous Saint-Venant model with surface tension and possible wall friction. contribution 0.95 0.84 0.07 asserted 1.00
s1 We define an appropriate weak solution notion for which we establish existence/uniqueness results with inputs that do not necessarily satisfy any compatibility condition as well as stabilization results with feedback laws that are constructed with the help of a Control Lyapunov Functional. contribution 0.68 0.95 0.10 asserted 1.00
s2 We show that the proposed family of stabilizing feedback laws is optimal for a certain meaningful quadratic cost functional. result 0.98 0.95 0.50 asserted 1.00
s3 Finally, we show that the optimal feedback law guarantees additional stronger stability estimates which are similar to those obtained in the case of classical solutions. result 0.99 0.94 0.26 asserted 1.00

What kind of paper the classifier reports this is: theoretical result 1.00 · evidence from proof or derivation 1.00.

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

This paper presents a complete inverse optimality study for a linearized tank-liquid system where the liquid is described by the viscous Saint-Venant model with surface tension and possible wall friction. We define an appropriate weak solution notion for which we establish existence/uniqueness results with inputs that do not necessarily satisfy any compatibility condition as well as stabilization results with feedback laws that are constructed with the help of a Control Lyapunov Functional. We show that the proposed family of stabilizing feedback laws is optimal for a certain meaningful quadratic cost functional. Finally, we show that the optimal feedback law guarantees additional stronger stability estimates which are similar to those obtained in the case of classical solutions.

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Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

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