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Dominant-Pole Placement for Predictor Synthesis

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Bryan Rojas-Ricca, Fernando Castaños, Sabine Mondié

Optimization and Control · Submitted 24 Jun 2023

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

The authors' main claim A comparative analysis is also presented, showing that our proposal achieves a better trade-off between delay and gain margin.

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arXiv ID2306.13828 (version 1)
Pith IDOCAANOWQ, Pith's permanent record of this paper and its review
CitationBryan Rojas-Ricca, Fernando Casta\~nos, Sabine Mondi\'e. "Dominant-Pole Placement for Predictor Synthesis." arXiv:2306.13828 (2023). https://pith.science/paper/OCAANOWQ
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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 4,796 input tokens.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.61 · human participants 0.02 · controlled comparison 0.47 · randomized assignment 0.01 · states quantitative result 0.05 · compares with prior results 0.89 · mentions code or data availability 0.02.

The abstract, sentence by sentence

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

This article analyzes the high-gain prediction approach for nonlinear input-delay systems. The problem is discussed in the light of weighted homogeneity and input-to-state stability. The canonical form for uniformly observable nonlinear systems allows tuning the spectrum of the linear part by multiplicity-induced dominance and ensures closed-loop system input-to-state stability using the descriptor method for Lyapunov-Krasovskii functionals. Due to the trade-off between delay and gain margin, a limitation of high-gain results for time-delay systems. The limitation is overcome by using a cascade of sub-predictors. A comparative analysis is also presented, showing that our proposal achieves a better trade-off between delay and gain margin.

background contribution method result interpretation main claim

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 article analyzes the high-gain prediction approach for nonlinear input-delay systems. contribution 0.73 0.70 0.04 asserted 0.91
s1 The problem is discussed in the light of weighted homogeneity and input-to-state stability. background 0.55 0.48 0.04 asserted 0.83
s2 The canonical form for uniformly observable nonlinear systems allows tuning the spectrum of the linear part by multiplicity-induced dominance and ensures closed-loop system input-to-state stability using the descriptor method for Lyapunov-Krasovskii functionals. method 0.62 0.62 0.42 asserted 1.00
s3 Due to the trade-off between delay and gain margin, a limitation of high-gain results for time-delay systems. limitation 0.57 0.19 0.07 asserted 0.78
s4 The limitation is overcome by using a cascade of sub-predictors. method 0.57 0.71 0.27 asserted 1.00
s5 A comparative analysis is also presented, showing that our proposal achieves a better trade-off between delay and gain margin. result 0.94 0.89 0.47 asserted 1.00

What kind of paper the classifier reports this is: method or tool 0.80 · evidence from proof or derivation 0.98.

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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 article analyzes the high-gain prediction approach for nonlinear input-delay systems. The problem is discussed in the light of weighted homogeneity and input-to-state stability. The canonical form for uniformly observable nonlinear systems allows tuning the spectrum of the linear part by multiplicity-induced dominance and ensures closed-loop system input-to-state stability using the descriptor method for Lyapunov-Krasovskii functionals. Due to the trade-off between delay and gain margin, a limitation of high-gain results for time-delay systems. The limitation is overcome by using a cascade of sub-predictors. A comparative analysis is also presented, showing that our proposal achieves a better trade-off between delay and gain margin.

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