{"id":"W2805038437","doi":"10.11159/cdsr18.113","title":"A New Integral Second-Order Terminal Sliding Mode Control with Time Delay Estimation for an Exoskeleton Robot with Dynamics Uncertainties","year":2018,"lang":"en","type":"article","venue":"Proceedings of the International Conference of Control, Dynamic systems, and Robotics","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"École de technologie supérieure","keywords":"Control theory (sociology); Exoskeleton; Computer science; Terminal sliding mode; Terminal (telecommunication); Dynamics (music); Sliding mode control; Robot; Control (management); Mode (computer interface); Control engineering; Engineering; Simulation; Artificial intelligence; Nonlinear system; Physics","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":[0.0002940771,0.000327806,0.0006271898,0.0001626821,0.00009162468,0.0001618674,0.000528048,0.0001272993,0.000007122178],"category_scores_gemma":[0.00009009834,0.0002227731,0.00007019832,0.000110229,0.0001870647,0.0005250812,0.00003246592,0.0001611029,9.273701e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001771549,"about_ca_system_score_gemma":0.0001650257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001490137,"about_ca_topic_score_gemma":0.0004627832,"domain_scores_codex":[0.9983885,0.00001533784,0.0006120244,0.0002762075,0.0004373562,0.0002705603],"domain_scores_gemma":[0.9970016,0.000134248,0.000525952,0.0001392392,0.00210061,0.00009832231],"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":[0.003468312,0.0001187624,0.005948502,0.001398972,0.002359945,0.000002221315,0.001435014,0.8467007,0.04022296,0.09358756,0.0002769812,0.004480097],"study_design_scores_gemma":[0.002902709,0.0007462363,0.0003533484,0.0007980321,0.0001948433,0.00009614697,0.0006132135,0.993495,0.000137042,0.0003677449,0.00003261686,0.0002630077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1149597,0.0001033443,0.8818116,0.0002873842,0.0004460344,0.001086279,0.0001734001,0.00008720015,0.001045077],"genre_scores_gemma":[0.9788516,0.000005341663,0.0200621,0.00001842953,0.0001978388,0.00004242595,0.00001967367,0.00005254531,0.0007500513],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8638919,"threshold_uncertainty_score":0.9084422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01293865655535108,"score_gpt":0.2393801987504665,"score_spread":0.2264415421951154,"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."}}