{"id":"W3113129710","doi":"10.1109/syscon47679.2020.9275829","title":"Adaptive Control of a Ball and Beam System","year":2020,"lang":"en","type":"article","venue":"2020 IEEE International Systems Conference (SysCon)","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Linear-quadratic regulator; Adaptive control; Control system; Ball (mathematics); Inner loop; Nonlinear system; Beam (structure); Engineering; Computer science; Optimal control; Mathematics; Control (management); Physics; Controller (irrigation); Mathematical optimization; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002524949,0.000298074,0.0006503339,0.00008902583,0.00003475616,0.0001550262,0.0003820905,0.0001329854,0.00003011771],"category_scores_gemma":[0.00007094503,0.0002930846,0.00009470832,0.0001305616,0.00006903513,0.0002650406,0.00003220353,0.0002656539,0.00009071157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001325975,"about_ca_system_score_gemma":0.00005317241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001252266,"about_ca_topic_score_gemma":0.000008352254,"domain_scores_codex":[0.9980539,0.0001514875,0.0007237922,0.0003628847,0.0004548582,0.0002530545],"domain_scores_gemma":[0.9987903,0.0001886596,0.0002418695,0.0001698397,0.0004192235,0.0001900642],"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":[0.00128925,0.0001441647,0.02749182,0.006711798,0.007825842,0.0005210844,0.01712436,0.3669328,0.3659286,0.1828126,0.0185178,0.00469983],"study_design_scores_gemma":[0.001618476,0.0001679506,0.0005412528,0.000627921,0.00004473745,0.0000553014,0.001249682,0.9870261,0.0008020373,0.000007073523,0.007533956,0.0003254929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2580753,0.003501164,0.6995907,0.00141648,0.008156602,0.002783134,0.0005571521,0.001984203,0.02393518],"genre_scores_gemma":[0.9988451,0.00002386954,0.00007917073,0.00005760572,0.0006698138,0.0001087849,0.00001085043,0.00005906454,0.0001457479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7407697,"threshold_uncertainty_score":0.9999521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01848689032246911,"score_gpt":0.2117413655696088,"score_spread":0.1932544752471397,"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."}}