{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:G2M2WAGWNX3TATO4OGTALSEQYX","short_pith_number":"pith:G2M2WAGW","schema_version":"1.0","canonical_sha256":"3699ab00d66df7304ddc71a605c890c5e5216fea1e0598686c932193985fd1e7","source":{"kind":"arxiv","id":"2605.17103","version":1},"attestation_state":"computed","paper":{"title":"Geometric Fault Identification via Mirror Descent Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SP"],"primary_cat":"eess.SY","authors_text":"Fred Y. Hadaegh, Haeyoon Han, Mahdi Taheri, Soon-Jo Chung","submitted_at":"2026-05-16T18:12:49Z","abstract_excerpt":"This paper develops a fault detection and identification (FDI) method for nonlinear control-affine systems under simultaneous actuator and sensor faults. We adopt a geometric approach to study the isolability of faults in the sense of the principal angles between subspaces corresponding to each actuator and sensor fault. As for the fault identification, a hybrid estimator that consists of a Luenberger-like observer with contraction guarantees is developed. Moreover, neural networks are embedded in the mentioned observer to estimate actuator and sensor faults. Considering that the training data"},"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":"2605.17103","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2026-05-16T18:12:49Z","cross_cats_sorted":["cs.SY","eess.SP"],"title_canon_sha256":"281c1ea4d4e5fc74461a474afaaf11e21b7c47ad5f69c3bee05fb62377957f4d","abstract_canon_sha256":"35d9195b013342f4de6497ae0cbc15aaa978514fe0908b84b5ae94d31dcc00c0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:03:40.209927Z","signature_b64":"Bue7ZPrkkDBBG0W2/LYioorO7wC6eBuHpAneMMOfm7eSxiKmKKangebGBCiHwmFMLyr3Z8FsKckFYHwXoX9BCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3699ab00d66df7304ddc71a605c890c5e5216fea1e0598686c932193985fd1e7","last_reissued_at":"2026-05-20T00:03:40.209201Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:03:40.209201Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Geometric Fault Identification via Mirror Descent Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SP"],"primary_cat":"eess.SY","authors_text":"Fred Y. Hadaegh, Haeyoon Han, Mahdi Taheri, Soon-Jo Chung","submitted_at":"2026-05-16T18:12:49Z","abstract_excerpt":"This paper develops a fault detection and identification (FDI) method for nonlinear control-affine systems under simultaneous actuator and sensor faults. We adopt a geometric approach to study the isolability of faults in the sense of the principal angles between subspaces corresponding to each actuator and sensor fault. As for the fault identification, a hybrid estimator that consists of a Luenberger-like observer with contraction guarantees is developed. Moreover, neural networks are embedded in the mentioned observer to estimate actuator and sensor faults. Considering that the training data"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17103","kind":"arxiv","version":1},"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/2605.17103/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T22:33:23.794228Z","status":"skipped","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T22:21:57.724801Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"bab337ad49aa331e29b9d40204033834fc2a52db16927d4a415c47543c870073"},"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":"2605.17103","created_at":"2026-05-20T00:03:40.209331+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.17103v1","created_at":"2026-05-20T00:03:40.209331+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17103","created_at":"2026-05-20T00:03:40.209331+00:00"},{"alias_kind":"pith_short_12","alias_value":"G2M2WAGWNX3T","created_at":"2026-05-20T00:03:40.209331+00:00"},{"alias_kind":"pith_short_16","alias_value":"G2M2WAGWNX3TATO4","created_at":"2026-05-20T00:03:40.209331+00:00"},{"alias_kind":"pith_short_8","alias_value":"G2M2WAGW","created_at":"2026-05-20T00:03:40.209331+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/G2M2WAGWNX3TATO4OGTALSEQYX","json":"https://pith.science/pith/G2M2WAGWNX3TATO4OGTALSEQYX.json","graph_json":"https://pith.science/api/pith-number/G2M2WAGWNX3TATO4OGTALSEQYX/graph.json","events_json":"https://pith.science/api/pith-number/G2M2WAGWNX3TATO4OGTALSEQYX/events.json","paper":"https://pith.science/paper/G2M2WAGW"},"agent_actions":{"view_html":"https://pith.science/pith/G2M2WAGWNX3TATO4OGTALSEQYX","download_json":"https://pith.science/pith/G2M2WAGWNX3TATO4OGTALSEQYX.json","view_paper":"https://pith.science/paper/G2M2WAGW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.17103&json=true","fetch_graph":"https://pith.science/api/pith-number/G2M2WAGWNX3TATO4OGTALSEQYX/graph.json","fetch_events":"https://pith.science/api/pith-number/G2M2WAGWNX3TATO4OGTALSEQYX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/G2M2WAGWNX3TATO4OGTALSEQYX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/G2M2WAGWNX3TATO4OGTALSEQYX/action/storage_attestation","attest_author":"https://pith.science/pith/G2M2WAGWNX3TATO4OGTALSEQYX/action/author_attestation","sign_citation":"https://pith.science/pith/G2M2WAGWNX3TATO4OGTALSEQYX/action/citation_signature","submit_replication":"https://pith.science/pith/G2M2WAGWNX3TATO4OGTALSEQYX/action/replication_record"}},"created_at":"2026-05-20T00:03:40.209331+00:00","updated_at":"2026-05-20T00:03:40.209331+00:00"}