{"id":"W3006129553","doi":"10.1016/j.automatica.2020.108863","title":"Distributed implementation of nonlinear model predictive control for AUV trajectory tracking","year":2020,"lang":"en","type":"article","venue":"Automatica","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":184,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Model predictive control; Robustness (evolution); Control theory (sociology); Computer science; Trajectory; Nonlinear system; Stability (learning theory); Control engineering; Engineering; Control (management); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005961304,0.0001055959,0.0002268605,0.0000261542,0.00002642969,0.000009588119,0.00007217926,0.0000446364,0.000008574617],"category_scores_gemma":[0.00006082772,0.0001124923,0.00005814626,0.00009295685,0.00001209811,0.000172151,0.000004591851,0.00004585567,0.000001790353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005120863,"about_ca_system_score_gemma":0.00002408593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001507617,"about_ca_topic_score_gemma":0.000002117192,"domain_scores_codex":[0.9992592,0.00001419477,0.0003597164,0.0001092959,0.0001083478,0.0001492755],"domain_scores_gemma":[0.9996007,0.00009228522,0.00008411914,0.0000877849,0.00008095962,0.00005416625],"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":[0.0000191276,0.000006686778,0.00005242127,0.0001569147,0.0000734614,1.880142e-7,0.0006039147,0.9888158,0.008167583,0.0001693337,0.0001653981,0.001769121],"study_design_scores_gemma":[0.00161722,0.00007471061,0.0003386161,0.00001746123,0.00006317656,3.201523e-7,0.0002257835,0.9946018,0.002807832,0.0001191858,0.00003954886,0.00009435617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01035989,0.0000339391,0.987464,0.0001189523,0.00004468705,0.0008038375,0.0006996287,0.0004044985,0.0000706042],"genre_scores_gemma":[0.9677023,0.000002023466,0.03192009,0.0000372325,0.00005677258,0.0001320684,0.0001173351,0.00003083228,0.000001327066],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9573424,"threshold_uncertainty_score":0.4587303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280029674179154,"score_gpt":0.2539415797570737,"score_spread":0.2411412830152822,"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."}}