{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:ZBF6Q2SEXS653V7XYOHNZIJAB2","short_pith_number":"pith:ZBF6Q2SE","schema_version":"1.0","canonical_sha256":"c84be86a44bcbdddd7f7c38edca1200ea2e03b15c596618112b0e4da2731be84","source":{"kind":"arxiv","id":"2108.08462","version":2},"attestation_state":"computed","paper":{"title":"$\\mathcal{L}_1$ Adaptive Control with Switched Reference Models: Application to Learn-to-Fly","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","math.OC"],"primary_cat":"eess.SY","authors_text":"Naira Hovakimyan, Pan Zhao, Steven Snyder","submitted_at":"2021-08-19T03:07:07Z","abstract_excerpt":"Learn-to-Fly (L2F) is a new framework that aims to replace the traditional iterative development paradigm for aerial vehicles with a combination of real-time aerodynamic modeling, guidance, and learning control. To ensure safe learning of the vehicle dynamics on the fly, this paper presents an $\\mathcal{L}_1$ adaptive control ($\\mathcal{L}_1$AC) based scheme, which actively estimates and compensates for the discrepancy between the intermediately learned dynamics and the actual dynamics. First, to incorporate the periodic update of the learned model within the L2F framework, this paper extends "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2108.08462","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2021-08-19T03:07:07Z","cross_cats_sorted":["cs.SY","math.OC"],"title_canon_sha256":"e3208110dd6fffc5bea213b863c7ae5f5301c3780627d53782e92cbff236791e","abstract_canon_sha256":"1dbe3b154e2931df5527e9fd27210d6029797b662eaf4ba903c2190629b8d68b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:46:11.866146Z","signature_b64":"nWJXU0wbgf/x4NxvIDlPrEVbrBIkbUl//B9YIfD8v1P+OJ+YrFw1C9LOcUEfe4BicsRuyrcnBgfLBTvLfXEgBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c84be86a44bcbdddd7f7c38edca1200ea2e03b15c596618112b0e4da2731be84","last_reissued_at":"2026-07-05T04:46:11.865782Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:46:11.865782Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"$\\mathcal{L}_1$ Adaptive Control with Switched Reference Models: Application to Learn-to-Fly","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","math.OC"],"primary_cat":"eess.SY","authors_text":"Naira Hovakimyan, Pan Zhao, Steven Snyder","submitted_at":"2021-08-19T03:07:07Z","abstract_excerpt":"Learn-to-Fly (L2F) is a new framework that aims to replace the traditional iterative development paradigm for aerial vehicles with a combination of real-time aerodynamic modeling, guidance, and learning control. To ensure safe learning of the vehicle dynamics on the fly, this paper presents an $\\mathcal{L}_1$ adaptive control ($\\mathcal{L}_1$AC) based scheme, which actively estimates and compensates for the discrepancy between the intermediately learned dynamics and the actual dynamics. First, to incorporate the periodic update of the learned model within the L2F framework, this paper extends "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.08462","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2108.08462/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2108.08462","created_at":"2026-07-05T04:46:11.865831+00:00"},{"alias_kind":"arxiv_version","alias_value":"2108.08462v2","created_at":"2026-07-05T04:46:11.865831+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.08462","created_at":"2026-07-05T04:46:11.865831+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZBF6Q2SEXS65","created_at":"2026-07-05T04:46:11.865831+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZBF6Q2SEXS653V7X","created_at":"2026-07-05T04:46:11.865831+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZBF6Q2SE","created_at":"2026-07-05T04:46:11.865831+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZBF6Q2SEXS653V7XYOHNZIJAB2","json":"https://pith.science/pith/ZBF6Q2SEXS653V7XYOHNZIJAB2.json","graph_json":"https://pith.science/api/pith-number/ZBF6Q2SEXS653V7XYOHNZIJAB2/graph.json","events_json":"https://pith.science/api/pith-number/ZBF6Q2SEXS653V7XYOHNZIJAB2/events.json","paper":"https://pith.science/paper/ZBF6Q2SE"},"agent_actions":{"view_html":"https://pith.science/pith/ZBF6Q2SEXS653V7XYOHNZIJAB2","download_json":"https://pith.science/pith/ZBF6Q2SEXS653V7XYOHNZIJAB2.json","view_paper":"https://pith.science/paper/ZBF6Q2SE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2108.08462&json=true","fetch_graph":"https://pith.science/api/pith-number/ZBF6Q2SEXS653V7XYOHNZIJAB2/graph.json","fetch_events":"https://pith.science/api/pith-number/ZBF6Q2SEXS653V7XYOHNZIJAB2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZBF6Q2SEXS653V7XYOHNZIJAB2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZBF6Q2SEXS653V7XYOHNZIJAB2/action/storage_attestation","attest_author":"https://pith.science/pith/ZBF6Q2SEXS653V7XYOHNZIJAB2/action/author_attestation","sign_citation":"https://pith.science/pith/ZBF6Q2SEXS653V7XYOHNZIJAB2/action/citation_signature","submit_replication":"https://pith.science/pith/ZBF6Q2SEXS653V7XYOHNZIJAB2/action/replication_record"}},"created_at":"2026-07-05T04:46:11.865831+00:00","updated_at":"2026-07-05T04:46:11.865831+00:00"}