{"id":"W4391330042","doi":"10.2514/6.2024-2281","title":"Composite Nonlinear Generalized Predictive Control for Spacecraft Formation Flying Under Disturbances","year":2024,"lang":"en","type":"article","venue":"","topic":"Spacecraft Dynamics and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Model predictive control; Spacecraft; Control theory (sociology); Nonlinear system; Composite number; Computer science; Control engineering; Control (management); Aerospace engineering; Engineering; Physics; Artificial intelligence; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002649381,0.0003380905,0.00031591,0.0001817271,0.0002267879,0.0004549501,0.0004422465,0.0002529098,0.0005548875],"category_scores_gemma":[0.0004585375,0.0001248776,0.0001877022,0.000200746,0.0003808859,0.000283843,0.0005189118,0.0004987013,0.00007168813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002808237,"about_ca_system_score_gemma":0.0004055781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002953851,"about_ca_topic_score_gemma":0.003038251,"domain_scores_codex":[0.9998617,0.00002138457,0.000005048479,0.0000228709,0.00007565987,0.00001330332],"domain_scores_gemma":[0.9998535,0.00004876671,0.00002822287,0.00001612861,0.0000454064,0.000007954146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001272283,0.00003673587,0.0003705188,0.0001250455,0.00002334068,0.0001436226,0.0001076757,0.8929326,0.01847203,0.01712946,0.0008892484,0.06964258],"study_design_scores_gemma":[0.000004747284,0.0000348427,0.0001295094,0.000002217437,0.000003162527,0.000007952799,0.000004548809,0.9963966,0.001085711,0.001840408,0.0004874108,0.000002914159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04689867,0.0003917374,0.9477923,0.0001029419,0.00007613545,0.00002279474,0.00001938879,0.0003234894,0.004372535],"genre_scores_gemma":[0.9731938,0.0002217645,0.02449348,0.00002620559,0.00002721896,0.00003712409,0.00003432238,0.00001151295,0.001954498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002953851,"threshold_uncertainty_score":0.005873322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006128129007805764,"score_gpt":0.2175833747739532,"score_spread":0.2114552457661475,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}