{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T11:05:32Z","timestamp":1768820732314,"version":"3.49.0"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2022,2,16]],"date-time":"2022-02-16T00:00:00Z","timestamp":1644969600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,2,16]],"date-time":"2022-02-16T00:00:00Z","timestamp":1644969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976172"],"award-info":[{"award-number":["61976172"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12002254"],"award-info":[{"award-number":["12002254"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Basic Research Plan in Shaanxi Province of China","award":["2020JQ-013"],"award-info":[{"award-number":["2020JQ-013"]}]},{"name":"Natural Science Basic Research Plan in Shaanxi Province of China","award":["2020JM-072"],"award-info":[{"award-number":["2020JM-072"]}]},{"name":"Science and Technology Development Fund, Macau SAR","award":["0018\/2019\/AKP"],"award-info":[{"award-number":["0018\/2019\/AKP"]}]},{"name":"Science and Technology Development Fund, Macau SAR","award":["SKL-IOTSC(UM)-2021-2023"],"award-info":[{"award-number":["SKL-IOTSC(UM)-2021-2023"]}]},{"name":"Zhuhai Science and Technology Innovation Bureau Zhuhai-Hong Kong-Macau Special Cooperation Project","award":["ZH22017002200001PWC"],"award-info":[{"award-number":["ZH22017002200001PWC"]}]},{"name":"Macao Young Scholar Program","award":["AM201909"],"award-info":[{"award-number":["AM201909"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Evolving Systems"],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1007\/s12530-022-09424-6","type":"journal-article","created":{"date-parts":[[2022,2,16]],"date-time":"2022-02-16T05:02:30Z","timestamp":1644987750000},"page":"637-651","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Adaptive nonparametric evolving fuzzy controller for uncertain nonlinear systems with dead zone"],"prefix":"10.1007","volume":"13","author":[{"given":"Zhao-Xu","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhi-Xin","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hai-Jun","family":"Rong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,2,16]]},"reference":[{"key":"9424_CR1","doi-asserted-by":"publisher","first-page":"20346","DOI":"10.1109\/ACCESS.2021.3054600","volume":"9","author":"C Aguilar-Ibanez","year":"2021","unstructured":"Aguilar-Ibanez C, Moreno-Valenzuela J, Garc\u00eda-Alarc\u00f3n O, Martinez-Lopez M, \u00c1ngel Acosta J, Suarez-Castanon MS (2021) PI-type controllers and $$\\Sigma$$-$$\\Delta$$ modulation for saturated DC-DC buck power converters. IEEE Access 9:20346\u201320357","journal-title":"IEEE Access"},{"key":"9424_CR2","doi-asserted-by":"publisher","first-page":"107764","DOI":"10.1016\/j.asoc.2021.107764","volume":"112","author":"KSTR Alves","year":"2021","unstructured":"Alves KSTR, de Aguiar EP (2021) A novel rule-based evolving fuzzy system applied to the thermal modeling of power transformers. Appl Soft Comput 112:107764","journal-title":"Appl Soft Comput"},{"key":"9424_CR3","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.asoc.2016.05.036","volume":"48","author":"G Andonovski","year":"2016","unstructured":"Andonovski G, Angelov P, Bla\u017ei\u010d\u010d S, \u0160krjanc I (2016) A practical implementation of robust evolving cloud-based controller with normalized data space for heat-exchanger plant. Appl Soft Comput 48:29\u201338","journal-title":"Appl Soft Comput"},{"issue":"9","key":"9424_CR4","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1515\/auto-2018-0024","volume":"66","author":"G Andonovski","year":"2018","unstructured":"Andonovski G, Costa BSJ, Bla\u017ei\u010d\u010d S, \u0160krjanc I (2018) Robust evolving controller for simulated surge tank and for real two-tank plant. at-Automatisierungstechnik 66(9):725\u2013734","journal-title":"at-Automatisierungstechnik"},{"issue":"9","key":"9424_CR5","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1515\/auto-2018-0024","volume":"66","author":"G Andonovski","year":"2018","unstructured":"Andonovski G, Costa BSJ, Bla\u017ei\u010d\u010d S, \u0160krjanc I (2018) Robust evolving controller for simulated surge tank and for real two-tank plant. at - Automatisierungstechnik 66(9):725\u2013734","journal-title":"at - Automatisierungstechnik"},{"key":"9424_CR6","doi-asserted-by":"crossref","unstructured":"Andonovski G, Angelov SBP, \u0160krjanc I (2015) Robust evolving cloud-based controller in normalized data space for heat-exchanger plant. In: 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp 1\u20137","DOI":"10.1109\/FUZZ-IEEE.2015.7337992"},{"key":"9424_CR7","doi-asserted-by":"publisher","DOI":"10.1002\/9781118481769","volume-title":"Autonomous Learning Systems: From Data Streams to Knowledge in Real-time","author":"P Angelov","year":"2012","unstructured":"Angelov P (2012) Autonomous Learning Systems: From Data Streams to Knowledge in Real-time. John Wiley and Sons, Chichester"},{"issue":"1","key":"9424_CR8","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1109\/TSMCB.2003.817053","volume":"34","author":"PP Angelov","year":"2004","unstructured":"Angelov PP, Filev DP (2004) An approach to online identification of takagi-sugeno fuzzy models. IEEE Trans Syst Man Cybern Part B (Cybernetics) 34(1):484\u2013498","journal-title":"IEEE Trans Syst Man Cybern Part B (Cybernetics)"},{"issue":"2","key":"9424_CR9","first-page":"163","volume":"41","author":"P Angelov","year":"2012","unstructured":"Angelov P, Yager R (2012) A new type of simplified fuzzy rule-based system. Int J Intell Syst 41(2):163\u2013185","journal-title":"Int J Intell Syst"},{"issue":"12","key":"9424_CR10","doi-asserted-by":"publisher","first-page":"1261","DOI":"10.1002\/int.21899","volume":"32","author":"P Angelov","year":"2017","unstructured":"Angelov P, K D, Gu X (2017) Empirical data analytics. Int J Intell Syst 32(12):1261\u20131284","journal-title":"Int J Intell Syst"},{"key":"9424_CR11","doi-asserted-by":"crossref","unstructured":"Angelov P, Buswell R (2001) Evolving rule-based models: A tool for intelligent adaptation. In: Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569), vol. 2, pp. 1062\u20131067","DOI":"10.1109\/NAFIPS.2001.944752"},{"issue":"6","key":"9424_CR12","doi-asserted-by":"publisher","first-page":"875","DOI":"10.1080\/00207728608926853","volume":"17","author":"JA Burton","year":"1986","unstructured":"Burton JA, Zinober ASI (1986) Continuous approximation of variable structure control, international journal of systems science. Int J Syst Sci 17(6):875\u2013885","journal-title":"Int J Syst Sci"},{"issue":"6","key":"9424_CR13","doi-asserted-by":"publisher","first-page":"1043","DOI":"10.1049\/iet-epa.2016.0819","volume":"11","author":"S-Y Chen","year":"2017","unstructured":"Chen S-Y, Liu T-S (2017) Intelligent tracking control of a PMLSM using self-evolving probabilistic fuzzy neural network. IET Electr Power Appl 11(6):1043\u20131054","journal-title":"IET Electr Power Appl"},{"issue":"5","key":"9424_CR14","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.1109\/72.950139","volume":"12","author":"JY Choi","year":"2001","unstructured":"Choi JY, Farrell JA (2001) Adaptive observer backstepping control using neural networks. IEEE Trans Neural Netw 12(5):1103\u20131112","journal-title":"IEEE Trans Neural Netw"},{"key":"9424_CR15","doi-asserted-by":"crossref","unstructured":"Costa B, Skrjanc I, Blazic S, Angelov P (2013) A practical implementation of self-evolving cloud-based control of a pilot plant. In: 2013 IEEE International Conference on Cybernetics (CYBCO), pp. 7\u201312","DOI":"10.1109\/CYBConf.2013.6617464"},{"key":"9424_CR16","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1016\/j.neucom.2021.04.065","volume":"451","author":"PV de Campos Souza","year":"2021","unstructured":"de Campos Souza PV, Lughofer E (2021) An evolving neuro-fuzzy system based on uni-nullneurons with advanced interpretability capabilities. Neurocomputing 451:231\u2013251","journal-title":"Neurocomputing"},{"key":"9424_CR17","doi-asserted-by":"publisher","first-page":"2357","DOI":"10.1007\/s00500-015-1946-4","volume":"21","author":"J de Jes\u00fas Rubio","year":"2017","unstructured":"de Jes\u00fas Rubio J, Bouchachia A (2017) MSAFIS: an evolving fuzzy inference system. Soft Comput 21:2357\u20132366","journal-title":"Soft Comput"},{"key":"9424_CR18","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1016\/j.ins.2021.05.018","volume":"569","author":"J de Jes\u00fas Rubio","year":"2021","unstructured":"de Jes\u00fas Rubio J, Lughofer E, Pieper J, Cruz P, Martinez DI, Ochoa G, Islas MA, Garcia E (2021) Adapting H-infinity controller for the desired reference tracking of the sphere position in the maglev process. Inf Sci 569:669\u2013686","journal-title":"Inf Sci"},{"issue":"1","key":"9424_CR19","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1109\/TCST.2008.2009644","volume":"18","author":"H Du","year":"2010","unstructured":"Du H, Zhang N, Ji JC, Gao W (2010) Robust fuzzy control of an active magnetic bearing subject to voltage saturation. IEEE Trans Control Syst Technol 18(1):164\u2013169","journal-title":"IEEE Trans Control Syst Technol"},{"key":"9424_CR20","doi-asserted-by":"crossref","unstructured":"Ferdaus MM, Pratama M, Anavatti SG, Garratt M (2018) A generic self-evolving neuro-fuzzy controller based high-performance hexacopter altitude control system. In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp 2784\u20132791","DOI":"10.1109\/SMC.2018.00475"},{"key":"9424_CR21","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1016\/j.ins.2019.10.001","volume":"512","author":"MM Ferdaus","year":"2020","unstructured":"Ferdaus MM, Pratama M, Anavatti SG, Garratt MA, Lughofer E (2020) Pac: A novel self-adaptive neuro-fuzzy controller for micro aerial vehicles. Inf Sci 512:481\u2013505","journal-title":"Inf Sci"},{"key":"9424_CR22","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.ins.2019.08.036","volume":"507","author":"D Ge","year":"2020","unstructured":"Ge D, Zeng X-J (2020) Learning data streams online-an evolving fuzzy system approach with self-learning\/adaptive thresholds. Inf Sci 507:172\u2013184","journal-title":"Inf Sci"},{"issue":"8","key":"9424_CR23","doi-asserted-by":"publisher","first-page":"2425","DOI":"10.1109\/TFUZZ.2020.2988846","volume":"29","author":"X Gu","year":"2021","unstructured":"Gu X (2021) Multilayer ensemble evolving fuzzy inference system. IEEE Trans Fuzzy Syst 29(8):2425\u20132431","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"9424_CR24","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","volume":"70","author":"GB Huang","year":"2006","unstructured":"Huang GB, Zhu QY, Siew CK (2006) Extreme learning machine: theory and applications. Neurocomputing 70:489\u2013501","journal-title":"Neurocomputing"},{"issue":"9","key":"9424_CR25","doi-asserted-by":"publisher","first-page":"1705","DOI":"10.1109\/9.788536","volume":"44","author":"Z-P Jiang","year":"1999","unstructured":"Jiang Z-P, Hill DJ (1999) A robust adaptive backstepping scheme for nonlinear systems with unmodeled dynamics. IEEE Trans Autom Control 44(9):1705\u20131711","journal-title":"IEEE Trans Autom Control"},{"issue":"4","key":"9424_CR26","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1109\/72.774232","volume":"10","author":"C-F Juang","year":"1999","unstructured":"Juang C-F, Lin C-T (1999) A recurrent self-organizing neural fuzzy inference network. IEEE Trans Neural Netw 10(4):828\u2013845","journal-title":"IEEE Trans Neural Netw"},{"issue":"2","key":"9424_CR27","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1109\/91.995117","volume":"10","author":"NK Kasabov","year":"2002","unstructured":"Kasabov NK, Song Q (2002) DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction. IEEE Trans Fuzzy Syst 10(2):144\u2013154","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"9424_CR28","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1016\/j.asoc.2018.08.022","volume":"73","author":"T-L Le","year":"2018","unstructured":"Le T-L, Lin C-M, Huynh T-T (2018) Self-evolving type-2 fuzzy brain emotional learning control design for chaotic systems using PSO. Appl Soft Comput 73:418\u2013433","journal-title":"Appl Soft Comput"},{"issue":"4","key":"9424_CR29","doi-asserted-by":"publisher","first-page":"923","DOI":"10.1109\/TFUZZ.2014.2333774","volume":"23","author":"D Leite","year":"2015","unstructured":"Leite D, Palhares RM, Campos VCS, Gomide F (2015) Evolving granular fuzzy model-based control of nonlinear dynamic systems. IEEE Trans Fuzzy Syst 23(4):923\u2013938","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"1","key":"9424_CR30","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1109\/TFUZZ.2010.2087381","volume":"19","author":"A Lemos","year":"2011","unstructured":"Lemos A, Caminhas W, Gomide F (2011) Multivariable Gaussian evolving fuzzy modeling system. IEEE Trans Fuzzy Syst 19(1):91\u2013104","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"9424_CR31","unstructured":"Li D-P, Liu Y-J, Tong S, Chen CLP, Li D-J (2018) Neural networks-based adaptive control for nonlinear state constrained systems with input delay. IEEE Trans Cybern, 1\u201310"},{"key":"9424_CR32","doi-asserted-by":"publisher","first-page":"2239","DOI":"10.1016\/j.neucom.2017.11.009","volume":"275","author":"C-M Lin","year":"2018","unstructured":"Lin C-M, Le T-L, Huynh T-T (2018) Self-evolving function-link interval type-2 fuzzy neural network for nonlinear system identification and control. Neurocomputing 275:2239\u20132250","journal-title":"Neurocomputing"},{"issue":"5","key":"9424_CR33","doi-asserted-by":"publisher","first-page":"1090","DOI":"10.1109\/TFUZZ.2016.2598360","volume":"25","author":"W Liu","year":"2017","unstructured":"Liu W, Lim C-C, Shi P, Xu S (2017) Backstepping fuzzy adaptive control for a class of quantized nonlinear systems. IEEE Trans Fuzzy Syst 25(5):1090\u20131101","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"6","key":"9424_CR34","doi-asserted-by":"publisher","first-page":"1393","DOI":"10.1109\/TFUZZ.2008.925908","volume":"16","author":"ED Lughofer","year":"2008","unstructured":"Lughofer ED (2008) FLEXFIS: A robust incremental learning approach for evolving Takagi-Sugeno fuzzy models. IEEE Trans Fuzzy Syst 16(6):1393\u20131410","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"4","key":"9424_CR35","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1007\/s12530-015-9132-6","volume":"6","author":"E Lughofer","year":"2015","unstructured":"Lughofer E, Cernuda C, Kindermann S, Pratama M (2015) Generalized smart evolving fuzzy systems. Evol Syst 6(4):269\u2013292","journal-title":"Evol Syst"},{"issue":"4","key":"9424_CR36","doi-asserted-by":"publisher","first-page":"1854","DOI":"10.1109\/TFUZZ.2017.2753727","volume":"26","author":"E Lughofer","year":"2018","unstructured":"Lughofer E, Pratama M, Skrjanc I (2018) Incremental rule splitting in generalized evolving fuzzy systems for autonomous drift compensation. IEEE Trans Fuzzy Syst 26(4):1854\u20131865","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"2","key":"9424_CR37","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1109\/TFUZZ.2016.2578338","volume":"25","author":"L Maciel","year":"2017","unstructured":"Maciel L, Ballini R, Gomide F (2017) Evolving possibilistic fuzzy modeling for realized volatility forecasting with jumps. IEEE Trans Fuzzy Syst 25(2):302\u2013314","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"9424_CR38","doi-asserted-by":"crossref","unstructured":"Mahmoud MS (2018) Basics of Fuzzy Control. Fuzzy Control, Estimation and Diagnosis: Single and Interconnected Systems, pp. 15\u201344. Springer, Cham","DOI":"10.1007\/978-3-319-54954-5_2"},{"key":"9424_CR39","doi-asserted-by":"crossref","unstructured":"Martinez DI, de Jes\u00fas Rubio J, Garcia V, Vargas TM, Islas MA, Pacheco J, Gutierrez GJ, Meda-Campa\u00f1a JA, Mujica-Vargas D, Aguilar-Iba\u00f1ez C (2021) Transformed structural properties method to determine the controllability and observability of robots. Appl Sci11(7)","DOI":"10.3390\/app11073082"},{"key":"9424_CR40","doi-asserted-by":"crossref","unstructured":"Martinez DI, Rubio JdJ, Aguilar A, Pacheco J, Gutierrez GJ, Garcia V, Vargas TM, Ochoa G, Cruz DR, Juarez CF (2020) Stabilization of two electricity generators. Complexity 2020","DOI":"10.1155\/2020\/8683521"},{"key":"9424_CR41","doi-asserted-by":"crossref","unstructured":"Mendes J, Maia R, Ara\u00fajo R, Souza FAA (2020) Self-evolving fuzzy controller composed of univariate fuzzy control rules. Appl Sci 10(17)","DOI":"10.3390\/app10175836"},{"key":"9424_CR42","doi-asserted-by":"publisher","first-page":"793","DOI":"10.1007\/s12555-017-0503-6","volume":"17","author":"DS Pires","year":"2019","unstructured":"Pires DS, de Oliveira Serra GL (2019) Methodology for evolving fuzzy Kalman filter identification. Int J Control Autom Syst 17:793\u2013800","journal-title":"Int J Control Autom Syst"},{"issue":"1","key":"9424_CR43","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1109\/TNNLS.2013.2271933","volume":"25","author":"M Pratama","year":"2014","unstructured":"Pratama M, Anavatti SG, Angelov PP, Lughofer E (2014) PANFIS: A novel incremental learning machine. IEEE Trans Neural Netw Learn Syst 25(1):55\u201368","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"3","key":"9424_CR44","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1109\/TFUZZ.2013.2264938","volume":"22","author":"M Pratama","year":"2014","unstructured":"Pratama M, Anavatti SG, Lughofer E (2014) GENEFIS: Toward an effective localist network. IEEE Trans Fuzzy Syst 22(3):547\u2013562","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"5","key":"9424_CR45","doi-asserted-by":"publisher","first-page":"1175","DOI":"10.1109\/TFUZZ.2016.2599855","volume":"25","author":"M Pratama","year":"2017","unstructured":"Pratama M, Lu J, Lughofer E, Zhang G, Er MJ (2017) An incremental learning of concept drifts using evolving type-2 recurrent fuzzy neural networks. IEEE Trans Fuzzy Syst 25(5):1175\u20131192","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"9424_CR46","doi-asserted-by":"crossref","unstructured":"Precup R-E, Bojan-Dragos C-A, Hedrea E-L, Rarinca M-D, Petriu EM (2017) Evolving fuzzy models for the position control of magnetic levitation systems. In: 2017 Evolving and Adaptive Intelligent Systems (EAIS), pp 1\u20136","DOI":"10.1109\/EAIS.2017.7954839"},{"key":"9424_CR47","doi-asserted-by":"crossref","unstructured":"Precup R-E, Radac M-B, Petriu EM, Roman R-C, Teban T-A, Szedlak-Stinean A-I (2016) Evolving fuzzy models for the position control of twin rotor aerodynamic systems. In: 2016 IEEE 14th International Conference on Industrial Informatics (INDIN), pp. 237\u2013242","DOI":"10.1109\/INDIN.2016.7819165"},{"issue":"7","key":"9424_CR48","doi-asserted-by":"publisher","first-page":"4625","DOI":"10.1109\/TIM.2020.2983531","volume":"69","author":"R-E Precup","year":"2020","unstructured":"Precup R-E, Teban T-A, Albu A, Borlea A-B, Zamfirache IA, Petriu M (2020) Evolving fuzzy models for prosthetic hand myoelectric-based control. IEEE Trans Instrum Meas 69(7):4625\u20134636","journal-title":"IEEE Trans Instrum Meas"},{"key":"9424_CR49","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.fss.2017.05.016","volume":"338","author":"OD Rocha Filho","year":"2018","unstructured":"Rocha Filho OD, de Oliveira Serra GL (2018) Recursive fuzzy instrumental variable based evolving neuro-fuzzy identification for non-stationary dynamic system in a noisy environment. Fuzzy Sets Syst 338:50\u201389","journal-title":"Fuzzy Sets Syst"},{"key":"9424_CR50","doi-asserted-by":"crossref","unstructured":"Rong H-J, Yang Z-X, Wong PK, Vong CM (2017) Adaptive self-learning fuzzy autopilot design for uncertain bank-to-turn missiles. J Dyn Syst Meas Control 139(4)","DOI":"10.1115\/1.4035091"},{"issue":"9","key":"9424_CR51","doi-asserted-by":"publisher","first-page":"1260","DOI":"10.1016\/j.fss.2005.12.011","volume":"157","author":"H-J Rong","year":"2006","unstructured":"Rong H-J, Sundararajan N, Huang G-B, Saratchandran P (2006) Sequential adaptive fuzzy inference system (SAFIS) for nonlinear system identification and prediction. Fuzzy Sets Syst 157(9):1260\u20131275","journal-title":"Fuzzy Sets Syst"},{"key":"9424_CR52","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1016\/j.neucom.2016.12.030","volume":"230","author":"H-J Rong","year":"2017","unstructured":"Rong H-J, Yang Z-X, Wong PK, Vong CM, Zhao G-S (2017) A novel meta-cognitive fuzzy-neural model with Backstepping strategy for adaptive control of uncertain nonlinear systems. Neurocomputing 230:332\u2013344","journal-title":"Neurocomputing"},{"issue":"5","key":"9424_CR53","doi-asserted-by":"publisher","first-page":"2774","DOI":"10.1109\/TFUZZ.2018.2793258","volume":"26","author":"H-J Rong","year":"2018","unstructured":"Rong H-J, Angelov PP, Gu X, Bai JM (2018) Stability of evolving fuzzy systems based on data clouds. IEEE Trans Fuzzy Syst 26(5):2774\u20132784","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"9424_CR54","doi-asserted-by":"publisher","first-page":"132191","DOI":"10.1109\/ACCESS.2021.3112575","volume":"9","author":"R Silva-Ortigoza","year":"2021","unstructured":"Silva-Ortigoza R, Hernandez-Marquez E, Roldan-Caballero A, Tavera-Mosqueda S, Silva-Ortigoza G (2021) Sensorless tracking control for a \u201cfull-bridge buck inverter-DC motor\u2019\u2019 system: Passivity and flatness-based design. IEEE Access 9:132191\u2013132204","journal-title":"IEEE Access"},{"key":"9424_CR55","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1016\/j.ins.2019.03.060","volume":"490","author":"I \u0160krjanc","year":"2019","unstructured":"\u0160krjanc I, Iglesias JA, Sanchis A, Leite D, Lughofer E, Gomide F (2019) Evolving fuzzy and neuro-fuzzy approaches in clustering, regression, identification, and classification: A survey. Inf Sci 490:344\u2013368","journal-title":"Inf Sci"},{"key":"9424_CR56","volume-title":"Applied Nonlinear Control","author":"JJE Slotine","year":"1991","unstructured":"Slotine JJE, Li WP (1991) Applied Nonlinear Control. Prentice-Hall, Englewood, Cliffs, New Jersey"},{"key":"9424_CR57","doi-asserted-by":"crossref","unstructured":"Soriano LA, Zamora E, Vazquez-Nicolas JM, Gerardo H, Balderas D (2020) PD control compensation based on a cascade neural network applied to a robot manipulator. Front Neurorobot 14","DOI":"10.3389\/fnbot.2020.577749"},{"key":"9424_CR58","doi-asserted-by":"crossref","unstructured":"Subramanian K, Suresh S, Babu RV (2012) Meta-cognitive neuro-fuzzy inference system for human emotion recognition. In: The 2012 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20137","DOI":"10.1109\/IJCNN.2012.6252678"},{"issue":"6","key":"9424_CR59","doi-asserted-by":"publisher","first-page":"910","DOI":"10.1109\/TCYB.2013.2276043","volume":"44","author":"S Tong","year":"2014","unstructured":"Tong S, Wang T, Li Y, Zhang H (2014) Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics. IEEE Trans Cybern 44(6):910\u2013921","journal-title":"IEEE Trans Cybern"},{"key":"9424_CR60","doi-asserted-by":"publisher","first-page":"14399","DOI":"10.1007\/s00521-019-04482-5","volume":"232","author":"PK Wong","year":"2020","unstructured":"Wong PK, Huang W, Vong CM, Yang Z (2020) Adaptive neural tracking control for automotive engine idle speed regulation using extreme learning machine. Neural Comput Appl 232:14399\u201314409","journal-title":"Neural Comput Appl"},{"key":"9424_CR61","doi-asserted-by":"crossref","unstructured":"Yang Z-X, Rong H-J, Angelov PP, Yang Z-X (2021) Statistically evolving fuzzy inference system for non-Gaussian noises. IEEE Trans Fuzzy Syst","DOI":"10.1109\/TFUZZ.2021.3090898"},{"issue":"5","key":"9424_CR62","doi-asserted-by":"publisher","first-page":"4508","DOI":"10.1109\/TIE.2020.2982094","volume":"68","author":"Z-X Yang","year":"2021","unstructured":"Yang Z-X, Rong H-J, Wong PK, Angelov P, Yang Z-X, Wang H (2021) Self-evolving data cloud-based PID-like controller for nonlinear uncertain systems. IEEE Trans Industr Electron 68(5):4508\u20134518","journal-title":"IEEE Trans Industr Electron"},{"issue":"106","key":"9424_CR63","first-page":"1915","volume":"15","author":"W Yue","year":"2021","unstructured":"Yue W, Wang Y, Li T, Yang Z (2021) A new fault tolerant control scheme for non-linear systems by T-S fuzzy model approach. IET Control Theory Appl 15(106):1915\u20131930","journal-title":"IET Control Theory Appl"},{"issue":"7","key":"9424_CR64","doi-asserted-by":"publisher","first-page":"1790","DOI":"10.1016\/j.automatica.2007.10.037","volume":"44","author":"J Zhou","year":"2008","unstructured":"Zhou J (2008) Decentralized adaptive control for large-scale time-delay systems with dead-zone input. Automatica 44(7):1790\u20131799","journal-title":"Automatica"}],"container-title":["Evolving Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-022-09424-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12530-022-09424-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-022-09424-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,9]],"date-time":"2022-09-09T19:58:39Z","timestamp":1662753519000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12530-022-09424-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,16]]},"references-count":64,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,10]]}},"alternative-id":["9424"],"URL":"https:\/\/doi.org\/10.1007\/s12530-022-09424-6","relation":{},"ISSN":["1868-6478","1868-6486"],"issn-type":[{"value":"1868-6478","type":"print"},{"value":"1868-6486","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,16]]},"assertion":[{"value":"10 November 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 January 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 February 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}