{"id":"W2126877763","doi":"10.1109/tmech.2007.892820","title":"A Robust Hybrid Intelligent Position/Force Control Scheme for Cooperative Manipulators","year":2007,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Ottawa","funders":"","keywords":"Control theory (sociology); Controller (irrigation); Computer science; Lyapunov stability; Fuzzy logic; Position (finance); Adaptive control; Control engineering; Lyapunov function; Parametric statistics; Robust control; Scheme (mathematics); A priori and a posteriori; Control system; Control (management); Engineering; Mathematics; Artificial intelligence; Nonlinear system","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009847269,0.0004532904,0.000478115,0.000324373,0.0005540192,0.000263159,0.0009417714,0.0001766997,0.00003952907],"category_scores_gemma":[0.00002256019,0.0004591823,0.0004045255,0.0004812421,0.00005704521,0.0006352893,0.000007428439,0.0004487261,0.0001855242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007172395,"about_ca_system_score_gemma":0.0002126704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003182856,"about_ca_topic_score_gemma":0.00007303821,"domain_scores_codex":[0.9967837,0.0001077221,0.0007793895,0.0008306924,0.00056125,0.0009372935],"domain_scores_gemma":[0.9977735,0.0003677226,0.0002271798,0.0008942658,0.0004109234,0.0003263859],"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":[0.0008764549,0.0017226,0.00002050834,0.0001404793,0.001266159,0.00008420843,0.0008107697,0.7282495,0.02305108,0.2080962,0.001362195,0.0343198],"study_design_scores_gemma":[0.004125015,0.0007907488,0.00001505845,0.00009100705,0.0001191529,0.00008239815,0.0002417607,0.9056557,0.0818015,0.000837241,0.005464471,0.0007759581],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003274546,0.0001466293,0.9910929,0.00078387,0.001986353,0.001796663,0.0003064004,0.0004691797,0.0001434927],"genre_scores_gemma":[0.9698805,0.00001868743,0.02842422,0.0005542805,0.0001346314,0.0002762668,0.00003657318,0.00005220295,0.000622649],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.966606,"threshold_uncertainty_score":0.999786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02812068825850511,"score_gpt":0.2540103922867407,"score_spread":0.2258897040282355,"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."}}