{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:YXTH452IZ2SMCF5QDASZ4ADBKV","short_pith_number":"pith:YXTH452I","schema_version":"1.0","canonical_sha256":"c5e67e7748cea4c117b018259e0061554492cb32a50a27b63fe960f9ba9f9649","source":{"kind":"arxiv","id":"1309.2024","version":1},"attestation_state":"computed","paper":{"title":"A Robust Continuous Time Fixed Lag Smoother for Nonlinear Uncertain Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Ian R. Petersen, Obaid Ur Rehman","submitted_at":"2013-09-09T01:11:10Z","abstract_excerpt":"This paper presents a robust fixed lag smoother for a class of nonlinear uncertain systems. A unified scheme, which combines a nonlinear robust estimator with a stable fixed lag smoother, is presented to improve the error covariance of the estimation. The robust fixed lag smoother is based on the use of Integral Quadratic Constraints and minimax LQG control. The state estimator uses a copy of the system nonlinearity in the estimator and combines an approximate model of the delayed states to produce a smoothed signal. In order to see the effectiveness of the method, it is applied to a quantum o"},"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":"1309.2024","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2013-09-09T01:11:10Z","cross_cats_sorted":[],"title_canon_sha256":"9b1fd8040a0e5a47fd92d5486fe56bbd3885bef6e5d70d70c2d67275affa9112","abstract_canon_sha256":"bd2ecca9beb20ebdddff8decdaf760cf3a92c6ad011fb725952a9b5d848d35ba"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:13:47.438453Z","signature_b64":"FhdGep+q3h4+NmnQdiLyGbQiRlKd/6IoTAK+ti+PGDAwglQ3ocXsX7SnEbOrvrFV20dbIXw4I0y5CI+qvGT0AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c5e67e7748cea4c117b018259e0061554492cb32a50a27b63fe960f9ba9f9649","last_reissued_at":"2026-05-18T03:13:47.437901Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:13:47.437901Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Robust Continuous Time Fixed Lag Smoother for Nonlinear Uncertain Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Ian R. Petersen, Obaid Ur Rehman","submitted_at":"2013-09-09T01:11:10Z","abstract_excerpt":"This paper presents a robust fixed lag smoother for a class of nonlinear uncertain systems. A unified scheme, which combines a nonlinear robust estimator with a stable fixed lag smoother, is presented to improve the error covariance of the estimation. The robust fixed lag smoother is based on the use of Integral Quadratic Constraints and minimax LQG control. The state estimator uses a copy of the system nonlinearity in the estimator and combines an approximate model of the delayed states to produce a smoothed signal. In order to see the effectiveness of the method, it is applied to a quantum o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1309.2024","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":""},"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":"1309.2024","created_at":"2026-05-18T03:13:47.437978+00:00"},{"alias_kind":"arxiv_version","alias_value":"1309.2024v1","created_at":"2026-05-18T03:13:47.437978+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1309.2024","created_at":"2026-05-18T03:13:47.437978+00:00"},{"alias_kind":"pith_short_12","alias_value":"YXTH452IZ2SM","created_at":"2026-05-18T12:28:09.283467+00:00"},{"alias_kind":"pith_short_16","alias_value":"YXTH452IZ2SMCF5Q","created_at":"2026-05-18T12:28:09.283467+00:00"},{"alias_kind":"pith_short_8","alias_value":"YXTH452I","created_at":"2026-05-18T12:28:09.283467+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2604.01730","citing_title":"Koopman-Based Nonlinear Identification and Adaptive Control of a Turbofan Engine","ref_index":47,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YXTH452IZ2SMCF5QDASZ4ADBKV","json":"https://pith.science/pith/YXTH452IZ2SMCF5QDASZ4ADBKV.json","graph_json":"https://pith.science/api/pith-number/YXTH452IZ2SMCF5QDASZ4ADBKV/graph.json","events_json":"https://pith.science/api/pith-number/YXTH452IZ2SMCF5QDASZ4ADBKV/events.json","paper":"https://pith.science/paper/YXTH452I"},"agent_actions":{"view_html":"https://pith.science/pith/YXTH452IZ2SMCF5QDASZ4ADBKV","download_json":"https://pith.science/pith/YXTH452IZ2SMCF5QDASZ4ADBKV.json","view_paper":"https://pith.science/paper/YXTH452I","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1309.2024&json=true","fetch_graph":"https://pith.science/api/pith-number/YXTH452IZ2SMCF5QDASZ4ADBKV/graph.json","fetch_events":"https://pith.science/api/pith-number/YXTH452IZ2SMCF5QDASZ4ADBKV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YXTH452IZ2SMCF5QDASZ4ADBKV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YXTH452IZ2SMCF5QDASZ4ADBKV/action/storage_attestation","attest_author":"https://pith.science/pith/YXTH452IZ2SMCF5QDASZ4ADBKV/action/author_attestation","sign_citation":"https://pith.science/pith/YXTH452IZ2SMCF5QDASZ4ADBKV/action/citation_signature","submit_replication":"https://pith.science/pith/YXTH452IZ2SMCF5QDASZ4ADBKV/action/replication_record"}},"created_at":"2026-05-18T03:13:47.437978+00:00","updated_at":"2026-05-18T03:13:47.437978+00:00"}