{"id":"W2126873307","doi":"10.1109/tia.2010.2090316","title":"An Adaptive-Filter-Based Torque-Ripple Minimization of a Fuzzy-Logic Controller for Speed Control of IPM Motor Drives","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Industry Applications","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Memorial University of Newfoundland","keywords":"Control theory (sociology); Direct torque control; Torque ripple; Torque; Vector control; Computer science; Filter (signal processing); Engineering; Control engineering; Induction motor; Voltage; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003285661,0.0003526594,0.0002877223,0.0002780941,0.0002806452,0.0003396662,0.0007169682,0.0003963358,0.0009230487],"category_scores_gemma":[0.0005475922,0.0001120342,0.0002614215,0.0001613371,0.0002136495,0.0002480091,0.0001505324,0.0004376958,0.0002028765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003030803,"about_ca_system_score_gemma":0.0002663892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001313441,"about_ca_topic_score_gemma":0.001867688,"domain_scores_codex":[0.9998063,0.00002199525,0.00001495796,0.00003767359,0.000106833,0.00001224413],"domain_scores_gemma":[0.9998422,0.0000409586,0.00002286738,0.00001492672,0.00007156596,0.000007562315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004505849,0.0001914297,0.000656852,0.0004984078,0.00009739342,0.0001897532,0.0001629761,0.08366844,0.2494079,0.005500323,0.001772116,0.6574039],"study_design_scores_gemma":[0.00006112334,0.0006460669,0.001048712,0.00002878464,0.00006482564,0.0002511689,0.00001323684,0.9309484,0.05952175,0.0008897647,0.006496201,0.0000299386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01654619,0.0002934199,0.9803381,0.00005086799,0.00006091691,0.00004892202,0.00001238688,0.0004824017,0.002166864],"genre_scores_gemma":[0.7488689,0.0002720302,0.2477122,0.0001298727,0.00009035261,0.000118713,0.00005103399,0.00004254029,0.002714395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001313441,"threshold_uncertainty_score":0.003087878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01524288271636777,"score_gpt":0.243907770425805,"score_spread":0.2286648877094372,"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."}}