{"id":"W2027184631","doi":"10.1109/cdc.2013.6760633","title":"A convex approach to stabilization of sampled-data piecewise affine slab systems","year":2013,"lang":"en","type":"article","venue":"","topic":"Stability and Control of Uncertain Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Convex optimization; Control theory (sociology); Controller (irrigation); Piecewise; Mathematics; Exponential stability; Stability (learning theory); Regular polygon; Piecewise linear function; Slab; Sampling (signal processing); Exponential function; Linear matrix inequality; Applied mathematics; Nonlinear system; Mathematical optimization; Computer science; Mathematical analysis; Engineering; Control (management); Physics; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.0003040096,0.0001522927,0.0003594484,0.00008101703,0.00002172277,0.00005913662,0.0004182013,0.00007943185,0.0001922168],"category_scores_gemma":[0.0001108833,0.0001306667,0.00003336224,0.0002682588,0.00002291435,0.0002808411,0.0000725747,0.00005978225,0.00009521232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005329078,"about_ca_system_score_gemma":0.0000201678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00133702,"about_ca_topic_score_gemma":0.00004974507,"domain_scores_codex":[0.9987792,0.00004538681,0.0004558791,0.0002595801,0.000229547,0.0002304329],"domain_scores_gemma":[0.9986411,0.0001211836,0.00003934433,0.0009298472,0.0001569775,0.0001115512],"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":[0.0001134781,0.000812494,0.01328737,0.006751023,0.0007989126,0.000001322166,0.005579601,0.701718,0.09884825,0.04888131,0.09220941,0.03099887],"study_design_scores_gemma":[0.0006229164,0.00005403825,0.00139693,0.00004527919,0.00002233818,0.000003097208,0.001608929,0.983166,0.000395934,0.00006853558,0.01234324,0.0002727396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1760565,0.001240759,0.7530468,0.0001740621,0.0008801421,0.003409762,0.0001685607,0.0007622159,0.06426127],"genre_scores_gemma":[0.9976881,0.000006089174,0.001602857,0.00002467365,0.00009944112,0.0001626189,0.00007249623,0.0000254896,0.0003182447],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8216316,"threshold_uncertainty_score":0.5328432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03381935338680096,"score_gpt":0.2148715458227596,"score_spread":0.1810521924359587,"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."}}