{"id":"W3002300989","doi":"10.1109/tsmc.2019.2962318","title":"Observed-Based Finite-Time Control of Nonlinear Semi-Markovian Jump Systems With Saturation Constraint","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Systems","topic":"Stability and Control of Uncertain Systems","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Program of Shanghai Academic Research Leader; Shanghai International Science and Technology; National Natural Science Foundation of China; Natural Science Foundation of Shanghai","keywords":"Control theory (sociology); Nonlinear system; Constraint (computer-aided design); Controller (irrigation); Interval (graph theory); Jump; Lyapunov function; Saturation (graph theory); Markov process; Computer science; Mathematics; Control (management); Mathematical optimization; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004517907,0.000571081,0.001203334,0.0001858825,0.0001464956,0.0002652922,0.0002594388,0.0003470301,0.00001333833],"category_scores_gemma":[0.00001822402,0.0005048247,0.0001840186,0.0003826981,0.0001876452,0.0001579179,0.000001433595,0.0004026523,0.0000459195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001394703,"about_ca_system_score_gemma":0.0001022796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004749247,"about_ca_topic_score_gemma":0.00003764002,"domain_scores_codex":[0.9966612,0.0003674845,0.001275185,0.0005515174,0.0006704287,0.0004741967],"domain_scores_gemma":[0.9977342,0.0007100439,0.0003146549,0.0005408925,0.0003007455,0.0003993943],"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":[0.0002683189,0.00007889928,0.0001563625,0.002483252,0.0004090769,0.0000166122,0.000544786,0.9905674,0.004930074,0.0001445995,0.00009295374,0.0003076462],"study_design_scores_gemma":[0.002961101,0.000740531,0.00003864307,0.001010885,0.0002182882,0.00003560595,0.00156871,0.9899909,0.0006844181,7.235756e-7,0.002198967,0.0005512247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05900868,0.003864217,0.9278319,0.0001744678,0.002226489,0.003575744,0.001091489,0.0007243334,0.001502715],"genre_scores_gemma":[0.9989759,0.00003705192,0.00005974038,0.00005353241,0.000272907,0.0002801482,0.000022171,0.0001000585,0.000198466],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9399672,"threshold_uncertainty_score":0.9997404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01428608145559817,"score_gpt":0.1792687313342965,"score_spread":0.1649826498786984,"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."}}