{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0007120296,0.0003694076,0.0004796334,0.0003863868,0.001495917,0.0003810789,0.0008285951,0.0001109105,0.00000869854],"category_scores_gemma":[0.00003896212,0.0004046259,0.0003572431,0.0005945371,0.00004183186,0.0004923976,0.000009725483,0.0003487909,0.00001631698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009128661,"about_ca_system_score_gemma":0.000120487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003248522,"about_ca_topic_score_gemma":0.0000370219,"domain_scores_codex":[0.9966466,0.0004089033,0.0009865032,0.0006416229,0.0006490396,0.0006672646],"domain_scores_gemma":[0.9976229,0.0008343762,0.0004345469,0.0006403314,0.0002876611,0.0001801626],"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":[0.0002348393,0.0003043132,0.00004596146,0.00007788274,0.0001495267,0.00001098973,0.0005022073,0.9438701,0.04609711,0.001142255,0.0001082657,0.0074566],"study_design_scores_gemma":[0.001881834,0.0002092914,0.00001285447,0.00007139935,0.00008038108,0.00007585592,0.0008042941,0.9406274,0.05419577,0.0000673134,0.001575089,0.0003985303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06029922,0.0001423649,0.9317015,0.0002626125,0.002587678,0.002023783,0.002457234,0.000517028,0.000008540757],"genre_scores_gemma":[0.9968532,0.000005934284,0.001984407,0.00009235057,0.00007222865,0.0008485928,0.0000618568,0.00004285358,0.00003860189],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.936554,"threshold_uncertainty_score":0.9998406,"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."}}