Set‐based gain‐scheduled control via quasi‐convex difference inclusions

[1]  Damiano Rotondo,et al.  State estimation and decoupling of unknown inputs in uncertain LPV systems using interval observers , 2018, Int. J. Control.

[2]  Antonio Sala,et al.  Polynomial Fuzzy Models for Nonlinear Control: A Taylor Series Approach , 2009, IEEE Transactions on Fuzzy Systems.

[3]  Herbert Werner,et al.  PCA-Based Parameter Set Mappings for LPV Models With Fewer Parameters and Less Overbounding , 2008, IEEE Transactions on Control Systems Technology.

[4]  Graziano Chesi,et al.  Estimating the domain of attraction for non-polynomial systems via LMI optimizations , 2009, Autom..

[5]  David Q. Mayne,et al.  Control of Constrained Dynamic Systems , 2001, Eur. J. Control.

[6]  Dapeng Xiong,et al.  Set-valued methods for linear parameter varying systems, , 1999, Autom..

[7]  Sophie Tarbouriech,et al.  Necessary and sufficient conditions for invariance of convex sets for discrete-time saturated systems , 2013, 52nd IEEE Conference on Decision and Control.

[9]  Antonio Sala,et al.  Optimisation of transient and ultimate inescapable sets with polynomial boundaries for nonlinear systems , 2016, Autom..

[10]  Wilson J. Rugh,et al.  Research on gain scheduling , 2000, Autom..

[11]  Johan Löfberg,et al.  YALMIP : a toolbox for modeling and optimization in MATLAB , 2004 .

[12]  Fernando D. Bianchi,et al.  Gain scheduling control of variable-speed wind energy conversion systems using quasi-LPV models , 2005 .

[13]  Antonio Sala,et al.  Cancellation-Based Nonquadratic Controller Design for Nonlinear Systems via Takagi–Sugeno Models , 2017, IEEE Transactions on Cybernetics.

[14]  D. Mayne,et al.  Computation of invariant sets for piecewise affine discrete time systems subject to bounded disturbances , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[15]  Eduardo F. Camacho,et al.  Invariant sets computation for convex difference inclusions systems , 2012, Syst. Control. Lett..

[16]  Manfred Morari,et al.  Multi-Parametric Toolbox 3.0 , 2013, 2013 European Control Conference (ECC).

[17]  Mazen Alamir,et al.  Iterative method for estimating the robust domains of attraction of non-linear systems: Application to cancer chemotherapy model with parametric uncertainties , 2019, Eur. J. Control.

[18]  A. Sala.  Generalising quasi-LPV and CDI models to Quasi-Convex Difference Inclusions , 2017 .

[19]  Antonio Sala,et al.  Performance-oriented quasi-LPV modeling of nonlinear systems , 2018, International Journal of Robust and Nonlinear Control.

[20]  Carsten W. Scherer,et al.  LMI Relaxations in Robust Control , 2006, Eur. J. Control.

[21]  Yi Shen,et al.  Zonotopic fault detection observer for linear parameter‐varying descriptor systems , 2019, International Journal of Robust and Nonlinear Control.

[22]  Antonio Sala,et al.  Asymptotically exact stabilisation for constrained discrete Takagi-Sugeno systems via set-invariance , 2017, Fuzzy Sets Syst..

[23]  Antonio Sala,et al.  On the conservativeness of fuzzy and fuzzy-polynomial control of nonlinear systems , 2009, Annu. Rev. Control..

[24]  A. Sala,et al.  Gain-Scheduled Control via Convex Nonlinear Parameter Varying Models , 2019, IFAC-PapersOnLine.

[25]  Franco Blanchini,et al.  Set invariance in control , 1999, Autom..

[26]  Fen Wu,et al.  Gain-scheduling control of LFT systems using parameter-dependent Lyapunov functions , 2005, Proceedings of the 2005, American Control Conference, 2005..

[27]  Antonio Sala,et al.  Stability analysis of LPV systems: Scenario approach , 2019, Automatica.

[28]  E. F. Camacho,et al.  On the computation of convex robust control invariant sets for nonlinear systems , 2010, Autom..

[29]  Thierry-Marie Guerra,et al.  LMI-based relaxed nonquadratic stabilization conditions for nonlinear systems in the Takagi-Sugeno's form , 2004, Autom..

[30]  Vicenç Puig,et al.  Interval observer versus set‐membership approaches for fault detection in uncertain systems using zonotopes , 2019, International Journal of Robust and Nonlinear Control.