{"id":"W1991340728","doi":"10.1109/icma.2007.4303718","title":"Sliding-Mode Observer Based Adaptive Control for Servo Actuator with Friction","year":2007,"lang":"en","type":"article","venue":"","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Actuator; Observer (physics); State observer; Servomotor; Servomechanism; Compensation (psychology); Controller (irrigation); Dynamical friction; Sliding mode control; Servo; Friction torque; Computer science; Adaptive control; Torque; Mode (computer interface); Control engineering; Engineering; Control (management); Nonlinear system; Artificial intelligence; Materials science; 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":[0.0002827564,0.0003181588,0.0004083038,0.0001616367,0.000174839,0.0003547692,0.0007171521,0.0004088113,0.0007555176],"category_scores_gemma":[0.0007025885,0.0001616196,0.0002830536,0.0001644101,0.0002727169,0.0004061731,0.000268719,0.0005876194,0.0001985171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002698785,"about_ca_system_score_gemma":0.0003486128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002673845,"about_ca_topic_score_gemma":0.00261552,"domain_scores_codex":[0.9998104,0.0000243189,0.00001384843,0.00003244064,0.00009967874,0.00001942627],"domain_scores_gemma":[0.9997622,0.00006935909,0.00003838616,0.00002456718,0.00009576741,0.000009681467],"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":[0.0006172828,0.0001578687,0.002376153,0.0006969401,0.0001824797,0.0005522228,0.0004857109,0.3381909,0.2353083,0.02437221,0.004282697,0.3927772],"study_design_scores_gemma":[0.00003544895,0.0001608512,0.0006756079,0.000009773242,0.00001957393,0.00006665067,0.00001105142,0.9854101,0.009393656,0.0007539546,0.003451537,0.00001180042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01836057,0.0005458604,0.9786851,0.00005267438,0.00009928028,0.00002169861,0.00001186562,0.0006413401,0.001581558],"genre_scores_gemma":[0.9424351,0.0004707652,0.05296272,0.0000525077,0.00004747523,0.00007150479,0.00006575505,0.00003154618,0.003862614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002673845,"threshold_uncertainty_score":0.005316615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01069321759003153,"score_gpt":0.2186156526359353,"score_spread":0.2079224350459038,"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."}}