Fuzzy functional observer for the control of the glucose-insulin system
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[1] Tyrone Fernando,et al. Functional Observability and the Design of Minimum Order Linear Functional Observers , 2010, IEEE Transactions on Automatic Control.
[2] Jianbin Qiu,et al. Adaptive Fuzzy Control for Nontriangular Structural Stochastic Switched Nonlinear Systems With Full State Constraints , 2019, IEEE Transactions on Fuzzy Systems.
[3] Shengyuan Xu,et al. Fuzzy Control System Design via Fuzzy Lyapunov Functions , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[4] Mohamed Darouach,et al. Generalized dynamic observer design for quasi-LPV systems , 2018, Autom..
[5] Mohamed Darouach. Existence and design of functional observers for linear systems , 2000, IEEE Trans. Autom. Control..
[6] Dragan Pamucar,et al. Portfolio model for analyzing human resources: An approach based on neuro-fuzzy modeling and the simulated annealing algorithm , 2017, Expert Syst. Appl..
[7] Alfredo Germani,et al. Mathematical Models and State Observation of the Glucose-Insulin Homeostasis , 2003, System Modelling and Optimization.
[8] Cheng-Liang Chen,et al. Modeling the physiological glucose-insulin system on normal and diabetic subjects , 2010, Comput. Methods Programs Biomed..
[9] Mohamed Darouach,et al. New unified H∞ dynamic observer design for linear systems with unknown inputs , 2016, Autom..
[10] Karolos M. Grigoriadis,et al. A unified algebraic approach to linear control design , 1998 .
[11] Horacio J. Marquez,et al. A frequency domain approach to state estimation , 2003, J. Frankl. Inst..
[12] Yin Zhenyu,et al. Hybrid controllability of linear switched systems , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).
[13] Dragan Pamucar,et al. Cost and risk aggregation in multi-objective route planning for hazardous materials transportation - A neuro-fuzzy and artificial bee colony approach , 2016, Expert Syst. Appl..
[14] Zhinong Miao,et al. A New Method for Fuzzy System Representation and Implementation , 2008, 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery.
[15] M. Fisher,et al. A semiclosed-loop algorithm for the control of blood glucose levels in diabetics , 1991, IEEE Transactions on Biomedical Engineering.
[16] Peng Shi,et al. Robust Constrained Control for MIMO Nonlinear Systems Based on Disturbance Observer , 2015, IEEE Transactions on Automatic Control.
[17] Mohamed Darouach,et al. H∞ dynamical observers design for linear descriptor systems. Application to state and unknown input estimation , 2015, Eur. J. Control.
[18] Tyrone Fernando,et al. Existence Conditions for Functional Observability From an Eigenspace Perspective , 2011, IEEE Transactions on Automatic Control.
[19] C. Cobelli,et al. Artificial Pancreas: Past, Present, Future , 2011, Diabetes.
[20] Dragan Pamucar,et al. Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network , 2016, Comput. Intell. Neurosci..
[21] J. Moreno,et al. Quasi-unknown input observers for linear systems , 2001, Proceedings of the 2001 IEEE International Conference on Control Applications (CCA'01) (Cat. No.01CH37204).
[22] Ligang Wu,et al. Event-triggered fuzzy control of nonlinear systems with its application to inverted pendulum systems , 2018, Autom..
[23] Kazuo Tanaka,et al. Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs , 1998, IEEE Trans. Fuzzy Syst..
[24] T. Taniguchi,et al. Model-based fuzzy control of TORA system: fuzzy regulator and fuzzy observer design via LMIs that represent decay rate, disturbance rejection, robustness, optimality , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).
[25] Dong Ryeol Shin,et al. Dynamic observers for linear time-invariant systems , 2002, Autom..
[26] D. Luenberger. Observers for multivariable systems , 1966 .
[27] Kazuo Tanaka,et al. A Sum-of-Squares Approach to Modeling and Control of Nonlinear Dynamical Systems With Polynomial Fuzzy Systems , 2009, IEEE Transactions on Fuzzy Systems.