{"id":"W2153148809","doi":"10.1002/rnc.1829","title":"Distributed consensus control for multi‐agent systems using terminal sliding mode and Chebyshev neural networks","year":2011,"lang":"en","type":"article","venue":"International Journal of Robust and Nonlinear Control","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Control theory (sociology); Terminal sliding mode; Artificial neural network; Controller (irrigation); Computer science; Sliding mode control; Nonlinear system; Tracking error; Lyapunov function; Bounded function; Mathematics; Control (management); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006296178,0.0003963615,0.0004770887,0.0002584254,0.0003013676,0.0006449761,0.0006124069,0.0006363819,0.0007677627],"category_scores_gemma":[0.0009389226,0.0001661035,0.000364322,0.0002462143,0.0005971441,0.0006427535,0.0006590972,0.0007281888,0.0001070735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006781571,"about_ca_system_score_gemma":0.0006745388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005891248,"about_ca_topic_score_gemma":0.002574195,"domain_scores_codex":[0.9997148,0.00006435355,0.00001704051,0.00007917525,0.00009550567,0.00002914],"domain_scores_gemma":[0.9996044,0.0001537321,0.00006717902,0.00003707056,0.0001160418,0.00002152526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004556254,0.00002048663,0.0002123015,0.00002778433,0.00002154904,0.00004440796,0.00003818608,0.9705144,0.004153564,0.006267273,0.000201221,0.01845318],"study_design_scores_gemma":[0.000002178933,0.00001047164,0.00003384881,8.507538e-7,0.000001231918,0.000002184526,0.000001899354,0.9988289,0.0002831876,0.0007650822,0.00006872664,0.000001409945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0504377,0.000235943,0.9463153,0.0001262542,0.00004327104,0.0000281858,0.00001360576,0.0001726945,0.002627039],"genre_scores_gemma":[0.97539,0.0001287017,0.02224589,0.00003388811,0.00001655021,0.00004379035,0.00002609023,0.00000956956,0.002105562],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005891248,"threshold_uncertainty_score":0.01171386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06533249496723814,"score_gpt":0.290897782951506,"score_spread":0.2255652879842679,"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."}}