{"id":"W2809191620","doi":"10.1139/tcsme-2017-0110","title":"A hybrid high-performance trajectory tracking controller for unmanned hexrotor with disturbance rejection","year":2018,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Robustness (evolution); Backstepping; Trajectory; Computer science; Control engineering; Controller (irrigation); Nonlinear system; Attitude control; Engineering; Adaptive control; Control (management); Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002358006,0.0003947933,0.0002686618,0.0001926324,0.0002698774,0.0003864382,0.000547882,0.0003330336,0.001296096],"category_scores_gemma":[0.0002755766,0.0001272494,0.0001677789,0.000148573,0.0001961916,0.0002918037,0.0003009349,0.0003275324,0.0003450694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000192977,"about_ca_system_score_gemma":0.0003475753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002119563,"about_ca_topic_score_gemma":0.001936356,"domain_scores_codex":[0.999797,0.00002109355,0.00001111531,0.00005048169,0.0001013546,0.00001902731],"domain_scores_gemma":[0.9998253,0.00002295423,0.00003930272,0.00001862728,0.00008226024,0.00001152797],"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":[0.000523885,0.0001333199,0.001361018,0.0004575607,0.0001149299,0.0005408119,0.0003744284,0.277369,0.339175,0.008737667,0.003189159,0.3680234],"study_design_scores_gemma":[0.00009489459,0.0006932536,0.001110928,0.00001943931,0.00002652287,0.0002517694,0.00003779202,0.9451157,0.0447573,0.0005334457,0.007330581,0.00002829828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03402887,0.0002006057,0.962216,0.00006171874,0.0000514547,0.00006575122,0.00003298255,0.001030414,0.002312156],"genre_scores_gemma":[0.8839471,0.0001473704,0.1108987,0.00007517652,0.00002904852,0.000122045,0.0001119152,0.00002915473,0.004639404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002119563,"threshold_uncertainty_score":0.00433588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00908863889146505,"score_gpt":0.1875387712472958,"score_spread":0.1784501323558307,"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."}}