{"id":"W7116699528","doi":"10.1109/joe.2025.3633535","title":"Model Predictive Control for Energy-Efficient Path Following Control of AUVs","year":2025,"lang":"","type":"article","venue":"IEEE Journal of Oceanic Engineering","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Convergence (economics); Model predictive control; Path (computing); Control theory (sociology); Energy (signal processing); Control (management); Trajectory; Lexicographical order; Motion planning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005211582,0.0007734674,0.0006744521,0.0002944211,0.0005347619,0.0008613836,0.0007795547,0.0006163729,0.001137431],"category_scores_gemma":[0.0009346028,0.0003492744,0.0004135585,0.0004164826,0.0006607043,0.0005427643,0.0009188881,0.001075284,0.0001696702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005448735,"about_ca_system_score_gemma":0.001126438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01242185,"about_ca_topic_score_gemma":0.008300656,"domain_scores_codex":[0.9997802,0.00004709925,0.00000855496,0.00004251509,0.00008168032,0.00003999526],"domain_scores_gemma":[0.9997557,0.0001031601,0.00004612559,0.0000133745,0.00007031536,0.00001132495],"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":[0.00002881453,0.0000135008,0.000136217,0.00005387871,0.00001315149,0.00004196658,0.00004821565,0.9784231,0.001485196,0.005783888,0.0004973566,0.01347476],"study_design_scores_gemma":[0.000003929178,0.00001856215,0.0000405967,0.000002874483,0.000003182088,0.000003456605,0.000005583397,0.9983671,0.0001975771,0.001069157,0.0002859604,0.000002050337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01898066,0.0006854721,0.9734385,0.0002735292,0.0001077006,0.00002822716,0.00003402083,0.0002603131,0.006191564],"genre_scores_gemma":[0.9784703,0.0004700461,0.01816513,0.00007184219,0.00004852147,0.00009480565,0.00005487312,0.00002326543,0.002601292],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01242185,"threshold_uncertainty_score":0.02469909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008748555043176563,"score_gpt":0.2213470969661664,"score_spread":0.2125985419229899,"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."}}