{"id":"W2785322937","doi":"10.1109/icus.2017.8278414","title":"Gain scheduling PID control of the quad-rotor helicopter","year":2017,"lang":"en","type":"article","venue":"2017 IEEE International Conference on Unmanned Systems (ICUS)","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Gain scheduling; PID controller; Control theory (sociology); Nonlinear system; Control engineering; Multivariable calculus; Scheduling (production processes); Engineering; Computer science; Rotor (electric); Control system; Control (management); Temperature control; Artificial intelligence","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":[0.0005274815,0.0003481205,0.0005398048,0.0001403801,0.0002557006,0.0003478499,0.001880655,0.0001922468,0.00007301438],"category_scores_gemma":[0.0002783095,0.0002633206,0.0002330608,0.00003558512,0.0001621126,0.0003369589,0.00007382347,0.0003599179,0.0003399063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001757448,"about_ca_system_score_gemma":0.00008064421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002310018,"about_ca_topic_score_gemma":0.00009918672,"domain_scores_codex":[0.9977138,0.0001329277,0.000727531,0.000347074,0.0007318039,0.0003468559],"domain_scores_gemma":[0.9973814,0.0001299971,0.000627704,0.001146395,0.0005999227,0.0001145956],"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":[0.00105376,0.0004964073,0.02058187,0.001040635,0.004104928,0.0001420757,0.001422414,0.2529849,0.5034099,0.1954599,0.01493649,0.004366764],"study_design_scores_gemma":[0.0029951,0.0001232455,0.006486879,0.001718943,0.00005035549,0.00003103695,0.0002696789,0.9725628,0.005675157,0.0001579549,0.009353814,0.0005750074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.599562,0.0009423812,0.09346781,0.004410205,0.05927784,0.005427627,0.001398653,0.000738239,0.2347753],"genre_scores_gemma":[0.9960202,0.00002107275,0.00006162112,0.00006320605,0.001312571,0.0001325959,0.000006299454,0.00005144937,0.002331006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.719578,"threshold_uncertainty_score":0.9999819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07406515547847196,"score_gpt":0.3041625353438178,"score_spread":0.2300973798653458,"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."}}