{
  "annotation_id": "25ef94a6-7e38-4e9b-83a3-27ec23436ab7",
  "date_created": "2026-02-17T05:53:24.111000Z",
  "date_modified": "2026-02-17T05:53:24.111000Z",
  "file_hash": "1806e560a8d53694bffe9a9fb89f9ed3c4eb1346777476d5a0347ad4891d617b",
  "private": false,
  "record": {
    "abstract": "This paper addresses the nonovershooting control problem for strict-feedback nonlinear systems with unknown control direction. We propose a method that integrates extremum seeking with Lie bracket-based design to achieve approximately nonovershooting tracking. The approach ensures that arbitrary reference trajectories can be tracked from below for any initial condition, with the overshoot reducible to arbitrarily small levels through parameter tuning. The method further provides a mechanism for enforcing high-relative-degree nonovershooting constraints in safety-critical scenarios involving unknown control directions.",
    "arxiv_id": "2601.09998",
    "authors": [
      "Kaixin Lu",
      "Ziliang Lyu",
      "Yanfang Mo",
      "Yiguang Hong",
      "Haoyong Yu"
    ],
    "categories": [
      "eess.SY",
      "cs.SY"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "title": "Extremum Seeking Nonovershooting Control of Strict-Feedback Systems Under Unknown Control Direction",
    "url": "https://arxiv.org/abs/2601.09998",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "65b80721-fdd0-409f-b137-8d4b23537a52",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}