{"id":"W4283212685","doi":"10.1109/tiv.2022.3175647","title":"Consensus Formation Tracking for Multiple AUV Systems Using Distributed Bioinspired Sliding Mode Control","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Vehicles","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Robustness (evolution); Sliding mode control; Nonlinear system; Lyapunov function; Computer science; Bounded function; Control engineering; Lyapunov stability; Controller (irrigation); Consensus; Engineering; Multi-agent system; Artificial intelligence; Mathematics; Control (management)","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":[0.0004894158,0.0004458183,0.0004014372,0.0002993006,0.000352079,0.0004549979,0.0008151372,0.0006691805,0.0005341402],"category_scores_gemma":[0.00077472,0.0001661452,0.0004304949,0.0002196043,0.0005405521,0.0005873235,0.0009330355,0.0004695209,0.00006856878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004341386,"about_ca_system_score_gemma":0.0006154517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00236481,"about_ca_topic_score_gemma":0.001621189,"domain_scores_codex":[0.9997577,0.00003471812,0.00001364526,0.00008970884,0.00008570949,0.00001857606],"domain_scores_gemma":[0.9996912,0.00008050782,0.00007714574,0.00003762115,0.00009294484,0.00002063652],"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":[0.00008538429,0.00008913872,0.001170213,0.0001398292,0.00006584924,0.0002065899,0.0002254534,0.8614398,0.0464524,0.009984959,0.0005117676,0.07962855],"study_design_scores_gemma":[0.00001237979,0.00008434081,0.0001414933,0.00000375164,0.000005744393,0.00001978991,0.00001080478,0.9958831,0.002044966,0.00143238,0.0003573452,0.00000394679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06685237,0.0002932837,0.929818,0.0001816314,0.00006901535,0.00003716351,0.00001524349,0.0002836151,0.002449609],"genre_scores_gemma":[0.9494007,0.0001733462,0.04895641,0.00005567054,0.00001578492,0.00008953699,0.00003002803,0.000008703415,0.001269888],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00236481,"threshold_uncertainty_score":0.004702091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05807405364990983,"score_gpt":0.2792586308240931,"score_spread":0.2211845771741833,"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."}}