{"id":"W4236160860","doi":"10.1504/ijmic.2019.10025570","title":"Vision-based leader-follower approach for uncertain quadrotor dynamics using feedback linearisation sliding mode control","year":2019,"lang":"en","type":"article","venue":"International Journal of Modelling Identification and Control","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Control theory (sociology); Differentiator; Payload (computing); Sliding mode control; Acceleration; Lyapunov function; Nonlinear system; Controller (irrigation); MATLAB; Computer science; Mode (computer interface); Position (finance); Control engineering; Engineering; Control (management); Artificial intelligence; Bandwidth (computing); Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002152191,0.0006568018,0.000610608,0.000180854,0.0003783671,0.000557958,0.0006994205,0.0006037557,0.001393851],"category_scores_gemma":[0.0002590891,0.0002424574,0.0003937893,0.0001409167,0.0003175851,0.0003974828,0.000537145,0.0005966113,0.0002924624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002918733,"about_ca_system_score_gemma":0.0003795238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003071717,"about_ca_topic_score_gemma":0.002435231,"domain_scores_codex":[0.9998529,0.00002246216,0.000007804068,0.00005532385,0.00004178896,0.00001966147],"domain_scores_gemma":[0.9998759,0.00003229071,0.00003149191,0.00001170301,0.00003657555,0.00001204023],"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":[0.0002925137,0.0001212847,0.001253126,0.0004805916,0.0001316491,0.0009721781,0.0004379243,0.757715,0.08446079,0.01143169,0.001883482,0.1408198],"study_design_scores_gemma":[0.00002069433,0.0002584591,0.0002622437,0.000007409247,0.00001154389,0.00007117046,0.00002906963,0.9944495,0.002727355,0.001064369,0.001089567,0.000008570812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02785501,0.0004954719,0.9668365,0.0001078665,0.0001046844,0.00004555723,0.00002285252,0.0003216076,0.004210519],"genre_scores_gemma":[0.9513075,0.0002425343,0.04357218,0.00006768191,0.00004157171,0.0000823167,0.00004413649,0.00002311439,0.004618839],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003071717,"threshold_uncertainty_score":0.006107688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02504305373850844,"score_gpt":0.312414987406508,"score_spread":0.2873719336679995,"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."}}