{"id":"W3084071890","doi":"10.1016/j.jfranklin.2020.09.001","title":"Continuous PID-SMC based on improved EHGO for robot manipulators with limited state measurements","year":2020,"lang":"en","type":"article","venue":"Journal of the Franklin Institute","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"China Scholarship Council","keywords":"Control theory (sociology); PID controller; Sliding mode control; Computer science; Lyapunov stability; Singular perturbation; Convergence (economics); Control engineering; Lyapunov function; State observer; Stability (learning theory); Engineering; Mathematics; Control (management); Nonlinear system; Artificial intelligence; Physics; Temperature control","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":[0.0003751253,0.0002503348,0.0004705736,0.0000853774,0.00008707467,0.00005384915,0.0004478598,0.00007044742,0.000005039209],"category_scores_gemma":[0.0002352039,0.0001585648,0.0002414693,0.0001945838,0.00004883059,0.0002086547,0.00001937379,0.0003666934,0.000007048154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001343717,"about_ca_system_score_gemma":0.0001092508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006288346,"about_ca_topic_score_gemma":0.00002665726,"domain_scores_codex":[0.9984991,0.0000510368,0.0005902136,0.0001411605,0.0004575476,0.0002609607],"domain_scores_gemma":[0.9988426,0.00007211044,0.0003575805,0.0002340304,0.0003187811,0.0001748711],"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":[0.001174188,0.00006148463,0.001732721,0.0001201005,0.000519326,0.00002797773,0.0001456578,0.9689471,0.02379304,0.00001377156,0.001581834,0.001882756],"study_design_scores_gemma":[0.0106988,0.001505505,0.00390638,0.0006280912,0.0003180743,0.00003364059,0.00004640708,0.9147299,0.01371403,0.00002358103,0.05389361,0.0005020081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2045518,0.0005389352,0.7832334,0.003023636,0.005495538,0.002245015,0.00007104854,0.0001966266,0.0006440362],"genre_scores_gemma":[0.9928394,0.000004274134,0.005612074,0.0007530857,0.0006568942,0.00001696163,0.000001874958,0.00006286211,0.00005257396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7882876,"threshold_uncertainty_score":0.6466085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04079231953017787,"score_gpt":0.2226508116632289,"score_spread":0.1818584921330511,"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."}}