{"id":"W2079784792","doi":"10.2316/journal.201.2007.4.201-1564","title":"FUZZY LOGIC BASED POSITION CONTROL OF A PMSM SERVO DRIVE","year":2007,"lang":"en","type":"article","venue":"Control and Intelligent Systems","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Lakehead University","funders":"","keywords":"Control theory (sociology); Vector control; Control engineering; Fuzzy logic; Servo drive; Controller (irrigation); Position (finance); PID controller; Computer science; Servomechanism; Electronic speed control; Servo control; Servo; Servomotor; Digital signal processor; Engineering; Digital signal processing; Control (management); Induction motor; Temperature control; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0005663994,0.0002602624,0.0005795557,0.000247828,0.00004701797,0.00003702134,0.0001378461,0.0001677661,0.00001321787],"category_scores_gemma":[0.00005879155,0.0002316715,0.000130662,0.0001727715,0.00005022377,0.00008422168,0.000005273396,0.0001590813,0.00002416435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001028589,"about_ca_system_score_gemma":0.00001706255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007060979,"about_ca_topic_score_gemma":0.00001149911,"domain_scores_codex":[0.9983507,0.00007002705,0.0006750888,0.0002297768,0.0002493283,0.0004250315],"domain_scores_gemma":[0.9989022,0.0003823804,0.0001378249,0.0002453922,0.0001677619,0.0001644118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00211974,0.0004300812,0.01906665,0.002039701,0.002227808,0.0002760864,0.0008311343,0.2916592,0.5885114,0.05049257,0.001684895,0.04066076],"study_design_scores_gemma":[0.00672434,0.0006486914,0.006665581,0.0003221019,0.0002832255,0.00006954304,0.0002612323,0.966776,0.01325631,0.0004074215,0.003881324,0.0007043071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1323632,0.01507159,0.8441211,0.000127695,0.00115019,0.001494807,0.00004356977,0.000315011,0.00531288],"genre_scores_gemma":[0.9993174,0.0000580807,0.00005681021,0.0001904174,0.0002350806,0.00003745701,0.000007117421,0.00003479185,0.00006282995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8669543,"threshold_uncertainty_score":0.944729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008221904898602181,"score_gpt":0.2057696315270408,"score_spread":0.1975477266284386,"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."}}