{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:EHTYLMS66L2XAADXHTDULORKYH","short_pith_number":"pith:EHTYLMS6","schema_version":"1.0","canonical_sha256":"21e785b25ef2f57000773cc745ba2ac1c3d1ecb9931731936e46b63990cdffe8","source":{"kind":"arxiv","id":"2403.14935","version":1},"attestation_state":"computed","paper":{"title":"Data-Driven Predictive Control with Adaptive Disturbance Attenuation for Constrained Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"math.OC","authors_text":"Hong Chen, Ilya Kolmanovsky, Nan Li","submitted_at":"2024-03-22T03:37:53Z","abstract_excerpt":"In this paper, we propose a novel data-driven predictive control approach for systems subject to time-domain constraints. The approach combines the strengths of H-infinity control for rejecting disturbances and MPC for handling constraints. In particular, the approach can dynamically adapt H-infinity disturbance attenuation performance depending on measured system state and forecasted disturbance level to satisfy constraints. We establish theoretical properties of the approach including robust guarantees of closed-loop stability, disturbance attenuation, constraint satisfaction under noisy dat"},"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":"2403.14935","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2024-03-22T03:37:53Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"4ea581a5c623c5d59145db4f20b7e3d3ad6b55ce6b74487568b3d418d624f1d1","abstract_canon_sha256":"9297a8bb653cbd266f61c301403aa1f6742a811d08b6e20b28802b566036e970"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:59:27.919743Z","signature_b64":"0D701JJ14Y87OCU5Xth6JZX50f+QASR2PqOlJJrj2dafbKB8/3whlHO9214Gqqr6OMwgfzUEIwozKQqYb67vBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"21e785b25ef2f57000773cc745ba2ac1c3d1ecb9931731936e46b63990cdffe8","last_reissued_at":"2026-07-05T07:59:27.919233Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:59:27.919233Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Data-Driven Predictive Control with Adaptive Disturbance Attenuation for Constrained Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"math.OC","authors_text":"Hong Chen, Ilya Kolmanovsky, Nan Li","submitted_at":"2024-03-22T03:37:53Z","abstract_excerpt":"In this paper, we propose a novel data-driven predictive control approach for systems subject to time-domain constraints. The approach combines the strengths of H-infinity control for rejecting disturbances and MPC for handling constraints. In particular, the approach can dynamically adapt H-infinity disturbance attenuation performance depending on measured system state and forecasted disturbance level to satisfy constraints. We establish theoretical properties of the approach including robust guarantees of closed-loop stability, disturbance attenuation, constraint satisfaction under noisy dat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.14935","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/2403.14935/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":"2403.14935","created_at":"2026-07-05T07:59:27.919293+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.14935v1","created_at":"2026-07-05T07:59:27.919293+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.14935","created_at":"2026-07-05T07:59:27.919293+00:00"},{"alias_kind":"pith_short_12","alias_value":"EHTYLMS66L2X","created_at":"2026-07-05T07:59:27.919293+00:00"},{"alias_kind":"pith_short_16","alias_value":"EHTYLMS66L2XAADX","created_at":"2026-07-05T07:59:27.919293+00:00"},{"alias_kind":"pith_short_8","alias_value":"EHTYLMS6","created_at":"2026-07-05T07:59:27.919293+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/EHTYLMS66L2XAADXHTDULORKYH","json":"https://pith.science/pith/EHTYLMS66L2XAADXHTDULORKYH.json","graph_json":"https://pith.science/api/pith-number/EHTYLMS66L2XAADXHTDULORKYH/graph.json","events_json":"https://pith.science/api/pith-number/EHTYLMS66L2XAADXHTDULORKYH/events.json","paper":"https://pith.science/paper/EHTYLMS6"},"agent_actions":{"view_html":"https://pith.science/pith/EHTYLMS66L2XAADXHTDULORKYH","download_json":"https://pith.science/pith/EHTYLMS66L2XAADXHTDULORKYH.json","view_paper":"https://pith.science/paper/EHTYLMS6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.14935&json=true","fetch_graph":"https://pith.science/api/pith-number/EHTYLMS66L2XAADXHTDULORKYH/graph.json","fetch_events":"https://pith.science/api/pith-number/EHTYLMS66L2XAADXHTDULORKYH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EHTYLMS66L2XAADXHTDULORKYH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EHTYLMS66L2XAADXHTDULORKYH/action/storage_attestation","attest_author":"https://pith.science/pith/EHTYLMS66L2XAADXHTDULORKYH/action/author_attestation","sign_citation":"https://pith.science/pith/EHTYLMS66L2XAADXHTDULORKYH/action/citation_signature","submit_replication":"https://pith.science/pith/EHTYLMS66L2XAADXHTDULORKYH/action/replication_record"}},"created_at":"2026-07-05T07:59:27.919293+00:00","updated_at":"2026-07-05T07:59:27.919293+00:00"}