{"id":"W4297515215","doi":"10.1007/s10846-022-01742-w","title":"A Fuzzy Logic-based Cascade Control without Actuator Saturation for the Unmanned Underwater Vehicle Trajectory Tracking","year":2022,"lang":"en","type":"article","venue":"Journal of Intelligent & Robotic Systems","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Kinematics; Actuator; Cascade; Backstepping; Robustness (evolution); Trajectory; Fuzzy logic; Engineering; Unmanned underwater vehicle; Control engineering; Torque; Underwater; Computer science; Adaptive control; Physics; 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":[0.001530094,0.0002844064,0.0006419595,0.0002107707,0.0002761351,0.0001412505,0.0004542212,0.00009012587,0.00002246857],"category_scores_gemma":[0.0001325452,0.0001940977,0.0003986929,0.0001678524,0.00003804812,0.000174962,0.00001742115,0.0005065512,0.000009668018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000709996,"about_ca_system_score_gemma":0.0001238577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002385509,"about_ca_topic_score_gemma":0.00001350767,"domain_scores_codex":[0.9973635,0.000295072,0.001150021,0.000173947,0.0006353466,0.0003821239],"domain_scores_gemma":[0.9977861,0.0009406465,0.0005666665,0.000258184,0.0003283667,0.0001200083],"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":[0.0003627072,0.00005344173,0.0001941438,0.0001081347,0.0004704495,0.00002345433,0.0004905583,0.9883073,0.00836184,0.000155267,0.0007565598,0.0007161358],"study_design_scores_gemma":[0.002084389,0.0007300836,0.000408883,0.000158027,0.0002888812,0.000286376,0.003178306,0.9843698,0.001453207,0.00004536021,0.006704334,0.0002923312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01911143,0.007214905,0.9658194,0.0006033565,0.005458174,0.001608316,0.00002507025,0.00009489921,0.00006449768],"genre_scores_gemma":[0.9977335,0.00001352893,0.0005273995,0.0001698602,0.001221921,0.0001232296,0.000004310891,0.00007877542,0.0001274483],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9786221,"threshold_uncertainty_score":0.7915074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03413415925585043,"score_gpt":0.2559574291648012,"score_spread":0.2218232699089508,"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."}}