{"id":"W2038029320","doi":"10.1109/systol.2013.6693853","title":"Fault-Tolerant Control Using &amp;#x210C;&lt;inf&gt;&amp;#x221E;&lt;/inf&gt; Sliding Mode Observer","year":2013,"lang":"en","type":"article","venue":"","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Control theory (sociology); Robustness (evolution); Fault tolerance; State observer; Sliding mode control; Computer science; Actuator; Nonlinear system; Control engineering; Engineering; Control (management); Physics; 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":[0.0002595992,0.0004630169,0.0005256141,0.0001814551,0.0002455209,0.0005948339,0.0006898239,0.0005129886,0.0007979018],"category_scores_gemma":[0.0006108638,0.000152186,0.0003441069,0.0001930397,0.000366019,0.0004784343,0.0003503312,0.0005936279,0.0001687187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000391666,"about_ca_system_score_gemma":0.0004594951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003116218,"about_ca_topic_score_gemma":0.002621033,"domain_scores_codex":[0.9997754,0.00002325455,0.00001572235,0.00004623506,0.0001112506,0.00002827811],"domain_scores_gemma":[0.9997553,0.0000568899,0.00006402412,0.00002991207,0.0000826656,0.0000111204],"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":[0.000471449,0.0001407396,0.001561653,0.0004071939,0.0001568741,0.0004866868,0.0005177939,0.5288837,0.1841343,0.01872347,0.002630472,0.2618857],"study_design_scores_gemma":[0.00002953087,0.0001984942,0.0004500479,0.000009724185,0.00002182519,0.00006864985,0.00001272391,0.9863263,0.01068336,0.0008422362,0.001347507,0.000009582697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03235257,0.0002674879,0.9643546,0.0000845508,0.00008325068,0.00003284751,0.00001567452,0.0006538092,0.002155253],"genre_scores_gemma":[0.9569136,0.000188482,0.04017153,0.00002813162,0.00002568463,0.00005961271,0.00003663132,0.00001456004,0.002561692],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003116218,"threshold_uncertainty_score":0.006196141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0369172370261086,"score_gpt":0.2501294758601671,"score_spread":0.2132122388340585,"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."}}