{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:HR4X5KGG35P5AFY2D6DDX4FDTA","short_pith_number":"pith:HR4X5KGG","schema_version":"1.0","canonical_sha256":"3c797ea8c6df5fd0171a1f863bf0a398399c2746ffe6d79c06ae2e98c985cb73","source":{"kind":"arxiv","id":"2504.16328","version":1},"attestation_state":"computed","paper":{"title":"Eigendecomposition Parameterization of Penalty Matrices for Enhanced Control Design: Aerospace Applications","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.RO","cs.SY","eess.SY"],"primary_cat":"math.OC","authors_text":"Ehsan Taheri, Nicholas P. Nurre","submitted_at":"2025-04-23T00:10:06Z","abstract_excerpt":"Modern control algorithms require tuning of square weight/penalty matrices appearing in quadratic functions/costs to improve performance and/or stability output. Due to simplicity in gain-tuning and enforcing positive-definiteness, diagonal penalty matrices are used extensively in control methods such as linear quadratic regulator (LQR), model predictive control, and Lyapunov-based control. In this paper, we propose an eigendecomposition approach to parameterize penalty matrices, allowing positive-definiteness with non-zero off-diagonal entries to be implicitly satisfied, which not only offers"},"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":"2504.16328","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2025-04-23T00:10:06Z","cross_cats_sorted":["cs.RO","cs.SY","eess.SY"],"title_canon_sha256":"37e532ae67cc5cb9908f4d2c87bab0f75595403e9b06dac4bbda8860891c7704","abstract_canon_sha256":"f944229c72d49e6bb95112cc2eb486622397bf1ef5ecea954824216a7885786c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:52:44.981031Z","signature_b64":"iOoi9Jx38cS6BneI7JfleQ0vtociav5Htbyl21DVpM7EtapuoM38r9GrISS1PESiO99ek73QRvwyrWMcXrA1BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3c797ea8c6df5fd0171a1f863bf0a398399c2746ffe6d79c06ae2e98c985cb73","last_reissued_at":"2026-07-05T10:52:44.980578Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:52:44.980578Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Eigendecomposition Parameterization of Penalty Matrices for Enhanced Control Design: Aerospace Applications","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.RO","cs.SY","eess.SY"],"primary_cat":"math.OC","authors_text":"Ehsan Taheri, Nicholas P. Nurre","submitted_at":"2025-04-23T00:10:06Z","abstract_excerpt":"Modern control algorithms require tuning of square weight/penalty matrices appearing in quadratic functions/costs to improve performance and/or stability output. Due to simplicity in gain-tuning and enforcing positive-definiteness, diagonal penalty matrices are used extensively in control methods such as linear quadratic regulator (LQR), model predictive control, and Lyapunov-based control. In this paper, we propose an eigendecomposition approach to parameterize penalty matrices, allowing positive-definiteness with non-zero off-diagonal entries to be implicitly satisfied, which not only offers"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.16328","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/2504.16328/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":"2504.16328","created_at":"2026-07-05T10:52:44.980629+00:00"},{"alias_kind":"arxiv_version","alias_value":"2504.16328v1","created_at":"2026-07-05T10:52:44.980629+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.16328","created_at":"2026-07-05T10:52:44.980629+00:00"},{"alias_kind":"pith_short_12","alias_value":"HR4X5KGG35P5","created_at":"2026-07-05T10:52:44.980629+00:00"},{"alias_kind":"pith_short_16","alias_value":"HR4X5KGG35P5AFY2","created_at":"2026-07-05T10:52:44.980629+00:00"},{"alias_kind":"pith_short_8","alias_value":"HR4X5KGG","created_at":"2026-07-05T10:52:44.980629+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/HR4X5KGG35P5AFY2D6DDX4FDTA","json":"https://pith.science/pith/HR4X5KGG35P5AFY2D6DDX4FDTA.json","graph_json":"https://pith.science/api/pith-number/HR4X5KGG35P5AFY2D6DDX4FDTA/graph.json","events_json":"https://pith.science/api/pith-number/HR4X5KGG35P5AFY2D6DDX4FDTA/events.json","paper":"https://pith.science/paper/HR4X5KGG"},"agent_actions":{"view_html":"https://pith.science/pith/HR4X5KGG35P5AFY2D6DDX4FDTA","download_json":"https://pith.science/pith/HR4X5KGG35P5AFY2D6DDX4FDTA.json","view_paper":"https://pith.science/paper/HR4X5KGG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2504.16328&json=true","fetch_graph":"https://pith.science/api/pith-number/HR4X5KGG35P5AFY2D6DDX4FDTA/graph.json","fetch_events":"https://pith.science/api/pith-number/HR4X5KGG35P5AFY2D6DDX4FDTA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HR4X5KGG35P5AFY2D6DDX4FDTA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HR4X5KGG35P5AFY2D6DDX4FDTA/action/storage_attestation","attest_author":"https://pith.science/pith/HR4X5KGG35P5AFY2D6DDX4FDTA/action/author_attestation","sign_citation":"https://pith.science/pith/HR4X5KGG35P5AFY2D6DDX4FDTA/action/citation_signature","submit_replication":"https://pith.science/pith/HR4X5KGG35P5AFY2D6DDX4FDTA/action/replication_record"}},"created_at":"2026-07-05T10:52:44.980629+00:00","updated_at":"2026-07-05T10:52:44.980629+00:00"}