Stubborn state observers for linear time-invariant systems

For the purpose of estimating the state of a linear time-invariant system with measurements subject to outliers, we propose an observer with a saturated output injection in such a way to mitigate the effect of abnormal and isolated measurement noise on the error dynamics. Stability conditions in both the continuous-time and the discrete-time cases are derived, which ensure global exponential stability to the origin for the error dynamics. Such conditions can be expressed in terms of linear matrix inequalities, allowing for a viable design by using convex optimization. The effectiveness of the approach is illustrated by means of simulations in comparison with the Luenberger observer.

[1]  Richard G. Gibbs,et al.  New Kalman filter and smoother consistency tests , 2013, Autom..

[2]  Luca Zaccarian,et al.  Results on stubborn Luenberger observers for linear time-invariant plants , 2015, 2015 European Control Conference (ECC).

[3]  Sophie Tarbouriech,et al.  Antiwindup design with guaranteed regions of stability: an LMI-based approach , 2005, IEEE Transactions on Automatic Control.

[4]  F. Clarke Optimization And Nonsmooth Analysis , 1983 .

[5]  R. Sanfelice,et al.  Hybrid dynamical systems , 2009, IEEE Control Systems.

[6]  D. Luenberger Observers for multivariable systems , 1966 .

[7]  Tingshu Hu,et al.  An analysis and design method for linear systems subject to actuator saturation and disturbance , 2002, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[8]  Luca Zaccarian,et al.  Anti-windup synthesis for linear control systems with input saturation: Achieving regional, nonlinear performance , 2008, Autom..

[9]  Lamine Mili,et al.  Robust Kalman Filter Based on a Generalized Maximum-Likelihood-Type Estimator , 2010, IEEE Transactions on Signal Processing.

[10]  Andrew R. Teel,et al.  On Assigning the Derivative of a Disturbance Attenuation Control Lyapunov Function , 2000, Math. Control. Signals Syst..

[11]  Weiyu Xu,et al.  System identification in the presence of outliers and random noises: A compressed sensing approach , 2014, Autom..

[12]  João Pedro Hespanha,et al.  Linear Systems Theory , 2009 .

[13]  D. Luenberger Observing the State of a Linear System , 1964, IEEE Transactions on Military Electronics.

[14]  Moti L. Tiku,et al.  Robust estimation in multiple linear regression model with non-Gaussian noise , 2008, Autom..

[15]  E. Yaz Linear Matrix Inequalities In System And Control Theory , 1998, Proceedings of the IEEE.

[16]  Eduardo Sontag An algebraic approach to bounded controllability of linear systems , 1984 .

[17]  Tingshu Hu,et al.  Control Systems with Actuator Saturation: Analysis and Design , 2001 .

[18]  Luca Zaccarian,et al.  Linear discrete-time global and regional anti-windup: an LMI approach , 2009, Int. J. Control.

[19]  Luca Zaccarian,et al.  Optimality-based dynamic allocation with nonlinear first-order redundant actuators , 2016, Eur. J. Control.

[20]  Daniele Astolfi,et al.  Low-power peaking-free high-gain observers for nonlinear systems , 2016, 2016 European Control Conference (ECC).

[21]  René Vidal,et al.  A continuous optimization framework for hybrid system identification , 2011, Autom..

[22]  Dragan Nesic,et al.  Parameter and State Estimation of Nonlinear Systems Using a Multi-Observer Under the Supervisory Framework , 2014, IEEE Transactions on Automatic Control.

[23]  Giovanni Indiveri,et al.  Output outlier robust state estimation , 2017 .

[24]  S. Tarbouriech,et al.  Anti-windup design with guaranteed regions of stability: an LMI-based approach , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[25]  Sophie Tarbouriech,et al.  Stability and Stabilization of Linear Systems with Saturating Actuators , 2011 .

[26]  Angelo Alessandri,et al.  Moving-horizon estimation with guaranteed robustness for discrete-time linear systems and measurements subject to outliers , 2016, Autom..

[27]  Wei Lin,et al.  A global observer for autonomous systems with bounded trajectories , 2007 .

[28]  Stephen P. Boyd,et al.  Linear Matrix Inequalities in Systems and Control Theory , 1994 .

[29]  Andrew R. Teel,et al.  Further variants of the Astolfi/Marconi high-gain observer , 2016, 2016 American Control Conference (ACC).

[30]  P. Olver Nonlinear Systems , 2013 .