{"id":"W2239986940","doi":"10.1016/s1474-6670(17)32349-2","title":"A Multi-Objective Output-Feedback Controller for Systems with Friction","year":2004,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Control theory (sociology); Servomechanism; Observer (physics); Controller (irrigation); Linear matrix inequality; Position (finance); Control engineering; Output feedback; Servo; Tracking error; Tracking (education); Feedback controller; Engineering; Computer science; Control (management); Mathematics; Mathematical optimization; Artificial intelligence; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001827033,0.0003426599,0.0005016167,0.0001530986,0.0001327485,0.0001572833,0.0001700578,0.0001623094,0.000001678336],"category_scores_gemma":[0.00008265761,0.0002937129,0.0001106876,0.0002103467,0.00005181259,0.0004537896,0.00001720213,0.0001824836,0.00006437726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003801561,"about_ca_system_score_gemma":0.00003928415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009026253,"about_ca_topic_score_gemma":0.00002185128,"domain_scores_codex":[0.9985521,0.000004455895,0.000352422,0.0003657354,0.0002543929,0.0004708953],"domain_scores_gemma":[0.9990766,0.00004159961,0.0001242929,0.00009226557,0.0005374541,0.0001277899],"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":[0.004867634,0.001488198,0.03735007,0.00702614,0.009306857,0.00006332636,0.03060626,0.6711628,0.175525,0.01683047,0.02385618,0.02191698],"study_design_scores_gemma":[0.01912194,0.001014067,0.008921993,0.0006957452,0.000248722,0.0001087761,0.005553166,0.9358811,0.002137491,0.000151488,0.02485927,0.001306243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2891537,0.003108336,0.6925337,0.0002015176,0.001778602,0.005854561,0.000144321,0.002660951,0.004564302],"genre_scores_gemma":[0.9869,0.000009904392,0.01059171,0.00002438854,0.0006183326,0.0006407211,0.000006647851,0.000118904,0.001089386],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6977463,"threshold_uncertainty_score":0.9999515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01447818923704378,"score_gpt":0.2150038134118581,"score_spread":0.2005256241748144,"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."}}