An easy design for interval observers

ABSTRACT This paper deals with the problem of interval estimation. The proposed approach is based on the use of successive derivatives in continuous time (or forward measurements in discrete time) in an algebraic (or local) interval observer. The main advantage of such an observer is that it relaxes the Metzler assumption widely used in the literature of cooperative interval observers. Moreover, no prior knowledge on the initial condition is needed, and no stability nor convergence issue do appear as the estimation is local. After introducing such an observer for Linear Time Variant (LTV) systems with bounded disturbances, some extensions are proposed for Linear Parameter Varying (LPV) systems as well as for functional systems and systems affected by Unknown Input (UI). Some examples illustrate the theoretical contributions.

[1]  Thierry Denoeux,et al.  State Estimation Using Interval Analysis and Belief-Function Theory: Application to Dynamic Vehicle Localization , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[2]  Denis V. Efimov,et al.  Interval State Estimation for a Class of Nonlinear Systems , 2012, IEEE Transactions on Automatic Control.

[3]  Denis V. Efimov,et al.  An effective method to interval observer design for time-varying systems , 2014, Autom..

[4]  Frédéric Mazenc,et al.  Interval observer composed of observers for nonlinear systems , 2014, 2014 European Control Conference (ECC).

[5]  Olivier Bernard,et al.  Interval observers for linear time-invariant systems with disturbances , 2011, Autom..

[6]  M. Boutayeb,et al.  Unknown Input Observer Synthesis Method with Modified H∞ Criteria for Nonlinear Systems Using Sobolev Norms , 2008 .

[7]  Arie Levant,et al.  Higher-order sliding modes, differentiation and output-feedback control , 2003 .

[8]  A. Levant Robust exact differentiation via sliding mode technique , 1998 .

[9]  Denis V. Efimov,et al.  Interval Observers for Time-Varying Discrete-Time Systems , 2013, IEEE Transactions on Automatic Control.

[10]  Thomas Reineking,et al.  Particle filtering in the Dempster-Shafer theory , 2011, Int. J. Approx. Reason..

[11]  Wilfrid Perruquetti,et al.  On interval observer design for time-invariant discrete-time systems , 2013, 2013 European Control Conference (ECC).

[12]  Olivier Bernard,et al.  Asymptotically Stable Interval Observers for Planar Systems With Complex Poles , 2010, IEEE Transactions on Automatic Control.

[13]  Eduardo F. Camacho,et al.  Guaranteed state estimation by zonotopes , 2005, Autom..

[14]  Dalil Ichalal,et al.  Interval observer for LPV systems with unknown inputs , 2017 .

[15]  Horacio J. Marquez,et al.  A novel approach to unknown input filter design for discrete-time linear systems , 2014, Autom..

[16]  Frédéric Mazenc,et al.  Interval observers for linear systems with additive disturbances , 2010 .

[17]  Denis V. Efimov,et al.  Interval observers for continuous-time LPV systems with L1/L2 performance , 2015, Autom..

[18]  Denis V. Efimov,et al.  Control of Nonlinear and LPV Systems: Interval Observer-Based Framework , 2013, IEEE Transactions on Automatic Control.

[19]  Leonid M. Fridman,et al.  Interval estimation for LPV systems applying high order sliding mode techniques , 2012, Autom..

[20]  Luc Jaulin,et al.  Nonlinear bounded-error state estimation of continuous-time systems , 2002, Autom..

[21]  Luc Jaulin,et al.  Applied Interval Analysis , 2001, Springer London.

[22]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[23]  Eric Walter,et al.  Set inversion via interval analysis for nonlinear bounded-error estimation , 1993, Autom..

[24]  D. Luenberger An introduction to observers , 1971 .

[25]  J. Norton,et al.  State bounding with ellipsoidal set description of the uncertainty , 1996 .

[26]  Olivier Bernard,et al.  Robust interval observers for global Lipschitz uncertain chaotic systems , 2010, Syst. Control. Lett..

[27]  Rong Su,et al.  Model Checking in Isomorphic Module Systems , 2019, IEEE Transactions on Automatic Control.

[28]  Denis V. Efimov,et al.  Interval state observer for nonlinear time varying systems , 2013, Autom..

[29]  Falin Wu,et al.  Ellipsoidal state-bounding-based set-membership estimation for linear system with unknown-but-bounded disturbances , 2016 .