{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:KSLW2ZOLFMNZKJ5JTG7AEA7QHI","short_pith_number":"pith:KSLW2ZOL","schema_version":"1.0","canonical_sha256":"54976d65cb2b1b9527a999be0203f03a2dece53c3e702532d3e4c00c03c7a8be","source":{"kind":"arxiv","id":"1907.10169","version":1},"attestation_state":"computed","paper":{"title":"Distributed Model Predictive Control Under Inexact Primal-Dual Gradient Optimization Based on Contraction Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Changyin Sun, Yang Shi, Yanxu Su","submitted_at":"2019-07-23T23:01:45Z","abstract_excerpt":"This paper develops a distributed model predictive control (DMPC) strategy for a class of discrete-time linear systems with consideration of globally coupled constraints. The DMPC under study is based on the dual problem concerning all subsystems, which is solved by means of the primal-dual gradient optimization in a distributed manner using Laplacian consensus. To reduce the computational burden, the constraint tightening method is utilized to provide a capability of premature termination with guaranteeing the convergence of the DMPC optimization. The contraction theory is first adopted in th"},"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":"1907.10169","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-07-23T23:01:45Z","cross_cats_sorted":[],"title_canon_sha256":"1e0bc90071b8e4480a5f192a5bf6916339fbc84a5b5971084bc6a5bf8422408e","abstract_canon_sha256":"25c6ae129cd9180c823350a4e0c21b20418e25814ffa352d3179d7683db6be73"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:38.824531Z","signature_b64":"ASmfQFIRT6WdLaZVaiUk5/ts5Tysu27imTmXKhS4X5B11wHXIXmwIilKCGUlLKHwMkaD3EwsJgmMAP4C88SgCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"54976d65cb2b1b9527a999be0203f03a2dece53c3e702532d3e4c00c03c7a8be","last_reissued_at":"2026-05-17T23:39:38.823818Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:38.823818Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Distributed Model Predictive Control Under Inexact Primal-Dual Gradient Optimization Based on Contraction Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Changyin Sun, Yang Shi, Yanxu Su","submitted_at":"2019-07-23T23:01:45Z","abstract_excerpt":"This paper develops a distributed model predictive control (DMPC) strategy for a class of discrete-time linear systems with consideration of globally coupled constraints. The DMPC under study is based on the dual problem concerning all subsystems, which is solved by means of the primal-dual gradient optimization in a distributed manner using Laplacian consensus. To reduce the computational burden, the constraint tightening method is utilized to provide a capability of premature termination with guaranteeing the convergence of the DMPC optimization. The contraction theory is first adopted in th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.10169","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":"1907.10169","created_at":"2026-05-17T23:39:38.823926+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.10169v1","created_at":"2026-05-17T23:39:38.823926+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.10169","created_at":"2026-05-17T23:39:38.823926+00:00"},{"alias_kind":"pith_short_12","alias_value":"KSLW2ZOLFMNZ","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_16","alias_value":"KSLW2ZOLFMNZKJ5J","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_8","alias_value":"KSLW2ZOL","created_at":"2026-05-18T12:33:21.387695+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/KSLW2ZOLFMNZKJ5JTG7AEA7QHI","json":"https://pith.science/pith/KSLW2ZOLFMNZKJ5JTG7AEA7QHI.json","graph_json":"https://pith.science/api/pith-number/KSLW2ZOLFMNZKJ5JTG7AEA7QHI/graph.json","events_json":"https://pith.science/api/pith-number/KSLW2ZOLFMNZKJ5JTG7AEA7QHI/events.json","paper":"https://pith.science/paper/KSLW2ZOL"},"agent_actions":{"view_html":"https://pith.science/pith/KSLW2ZOLFMNZKJ5JTG7AEA7QHI","download_json":"https://pith.science/pith/KSLW2ZOLFMNZKJ5JTG7AEA7QHI.json","view_paper":"https://pith.science/paper/KSLW2ZOL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.10169&json=true","fetch_graph":"https://pith.science/api/pith-number/KSLW2ZOLFMNZKJ5JTG7AEA7QHI/graph.json","fetch_events":"https://pith.science/api/pith-number/KSLW2ZOLFMNZKJ5JTG7AEA7QHI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KSLW2ZOLFMNZKJ5JTG7AEA7QHI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KSLW2ZOLFMNZKJ5JTG7AEA7QHI/action/storage_attestation","attest_author":"https://pith.science/pith/KSLW2ZOLFMNZKJ5JTG7AEA7QHI/action/author_attestation","sign_citation":"https://pith.science/pith/KSLW2ZOLFMNZKJ5JTG7AEA7QHI/action/citation_signature","submit_replication":"https://pith.science/pith/KSLW2ZOLFMNZKJ5JTG7AEA7QHI/action/replication_record"}},"created_at":"2026-05-17T23:39:38.823926+00:00","updated_at":"2026-05-17T23:39:38.823926+00:00"}