Optimisation of transient and ultimate inescapable sets with polynomial boundaries for nonlinear systems

This paper addresses the problem of bounding the trajectories of nonlinear systems (transient and ultimate bounds) from initial conditions in given sets, when subject to possibly nonvanishing disturbances constrained by some finite-interval integral bounds, with a suitable controller. The so-called robustly-inescapable sets are determined from such initial conditions and disturbance bounds. In order to get numerical results, the approach considers embedding the nonlinear dynamics in a convex combination of polynomials, and solving sum-of-squares (SOS) problems on them, optimising some inescapable-set size parameters. Determination of approximate (locally) optimal solutions usually requires an iterative evaluation of SOS problems, because of products of decision variables.

[1]  A. Papachristodoulou,et al.  Generalised absolute stability and Sum of Squares , 2011 .

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

[3]  P. Peres,et al.  Robust filtering with guaranteed energy-to-peak performance — an LMI approach , 1999 .

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

[5]  María M. Seron,et al.  Bounds and invariant sets for a class of switching systems with delayed-state-dependent perturbations , 2013, Autom..

[6]  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).

[7]  José A. De Doná,et al.  Probabilistic set invariance and ultimate boundedness , 2012, Autom..

[8]  Reinaldo M. Palhares,et al.  Robust filtering with guaranteed energy-to-peak performance - an LM1 approach , 2000, Autom..

[9]  Charalampos P. Bechlioulis,et al.  Adaptive control with guaranteed transient and steady state tracking error bounds for strict feedback systems , 2009, Autom..

[10]  M. Sznaier,et al.  Persistent disturbance rejection via static-state feedback , 1995, IEEE Trans. Autom. Control..

[11]  G. Stengle A nullstellensatz and a positivstellensatz in semialgebraic geometry , 1974 .

[12]  Antonio Sala,et al.  Closed-Form Estimates of the Domain of Attraction for Nonlinear Systems via Fuzzy-Polynomial Models , 2014, IEEE Transactions on Cybernetics.

[13]  K. Poolla,et al.  A linear matrix inequality approach to peak‐to‐peak gain minimization , 1996 .

[14]  G. Chesi Domain of Attraction: Analysis and Control via SOS Programming , 2011 .

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

[16]  Zongli Lin,et al.  Set invariance analysis and gain-scheduling control for LPV systems subject to actuator saturation , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[17]  Michel Verhaegen,et al.  Robust output-feedback controller design via local BMI optimization , 2004, Autom..

[18]  P. Gahinet,et al.  A linear matrix inequality approach to H∞ control , 1994 .

[19]  Andrew Packard,et al.  Control Applications of Sum of Squares Programming , 2005 .

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

[21]  Jeff S. Shamma,et al.  Analysis and design of gain scheduled control systems , 1988 .

[22]  Sergio García-Nieto,et al.  Stabilization conditions of fuzzy systems under persistent perturbations and their application in nonlinear systems , 2008, Eng. Appl. Artif. Intell..