{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:C3XP4OUOUOAR5RJJ4BJ5FDPDDA","short_pith_number":"pith:C3XP4OUO","schema_version":"1.0","canonical_sha256":"16eefe3a8ea3811ec529e053d28de31826a630f1e7261c342cfd5848359f849e","source":{"kind":"arxiv","id":"1603.03677","version":1},"attestation_state":"computed","paper":{"title":"Self-triggered Model Predictive Control for Nonlinear Input-Affine Dynamical Systems via Adaptive Control Samples Selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Dimos.V.Dimarogonas, Kazumune Hashimoto, Shuichi Adachi","submitted_at":"2016-03-11T16:09:24Z","abstract_excerpt":"In this paper, we propose a self-triggered formulation of Model Predictive Control for continuous-time nonlinear input-affine networked control systems. Our control method specifies not only when to execute control tasks but also provides a way to discretize the optimal control trajectory into several control samples, so that the reduction of communication load will be obtained. Stability analysis under the sample-and-hold implementation is also given, which guarantees that the state converges to a terminal region where the system can be stabilized by a local state feedback controller. Some si"},"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":"1603.03677","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2016-03-11T16:09:24Z","cross_cats_sorted":[],"title_canon_sha256":"1956f846eb687457caecef3114c6a3c804cee13da8750a441ca8ae481d04d9c2","abstract_canon_sha256":"a34555bfa974eecbc0f925181ef0e890c887e12975ccdefe123c7ef4e87d4266"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:58:33.940521Z","signature_b64":"V83XWefjaNYRTzFSy0HBKqL2k4J4US4dzaFFOgKUhfuVX7tSKoTrlPQjZTHnIMzWdHw2SyxkhmVzjj2cUUDjAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"16eefe3a8ea3811ec529e053d28de31826a630f1e7261c342cfd5848359f849e","last_reissued_at":"2026-05-18T00:58:33.939879Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:58:33.939879Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Self-triggered Model Predictive Control for Nonlinear Input-Affine Dynamical Systems via Adaptive Control Samples Selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Dimos.V.Dimarogonas, Kazumune Hashimoto, Shuichi Adachi","submitted_at":"2016-03-11T16:09:24Z","abstract_excerpt":"In this paper, we propose a self-triggered formulation of Model Predictive Control for continuous-time nonlinear input-affine networked control systems. Our control method specifies not only when to execute control tasks but also provides a way to discretize the optimal control trajectory into several control samples, so that the reduction of communication load will be obtained. Stability analysis under the sample-and-hold implementation is also given, which guarantees that the state converges to a terminal region where the system can be stabilized by a local state feedback controller. Some si"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.03677","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":"1603.03677","created_at":"2026-05-18T00:58:33.939970+00:00"},{"alias_kind":"arxiv_version","alias_value":"1603.03677v1","created_at":"2026-05-18T00:58:33.939970+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.03677","created_at":"2026-05-18T00:58:33.939970+00:00"},{"alias_kind":"pith_short_12","alias_value":"C3XP4OUOUOAR","created_at":"2026-05-18T12:30:09.641336+00:00"},{"alias_kind":"pith_short_16","alias_value":"C3XP4OUOUOAR5RJJ","created_at":"2026-05-18T12:30:09.641336+00:00"},{"alias_kind":"pith_short_8","alias_value":"C3XP4OUO","created_at":"2026-05-18T12:30:09.641336+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/C3XP4OUOUOAR5RJJ4BJ5FDPDDA","json":"https://pith.science/pith/C3XP4OUOUOAR5RJJ4BJ5FDPDDA.json","graph_json":"https://pith.science/api/pith-number/C3XP4OUOUOAR5RJJ4BJ5FDPDDA/graph.json","events_json":"https://pith.science/api/pith-number/C3XP4OUOUOAR5RJJ4BJ5FDPDDA/events.json","paper":"https://pith.science/paper/C3XP4OUO"},"agent_actions":{"view_html":"https://pith.science/pith/C3XP4OUOUOAR5RJJ4BJ5FDPDDA","download_json":"https://pith.science/pith/C3XP4OUOUOAR5RJJ4BJ5FDPDDA.json","view_paper":"https://pith.science/paper/C3XP4OUO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1603.03677&json=true","fetch_graph":"https://pith.science/api/pith-number/C3XP4OUOUOAR5RJJ4BJ5FDPDDA/graph.json","fetch_events":"https://pith.science/api/pith-number/C3XP4OUOUOAR5RJJ4BJ5FDPDDA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/C3XP4OUOUOAR5RJJ4BJ5FDPDDA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/C3XP4OUOUOAR5RJJ4BJ5FDPDDA/action/storage_attestation","attest_author":"https://pith.science/pith/C3XP4OUOUOAR5RJJ4BJ5FDPDDA/action/author_attestation","sign_citation":"https://pith.science/pith/C3XP4OUOUOAR5RJJ4BJ5FDPDDA/action/citation_signature","submit_replication":"https://pith.science/pith/C3XP4OUOUOAR5RJJ4BJ5FDPDDA/action/replication_record"}},"created_at":"2026-05-18T00:58:33.939970+00:00","updated_at":"2026-05-18T00:58:33.939970+00:00"}