Adaptive Constrained Control of Uncertain ARMA-Systems based on Set Membership Identification

In this article an adaptive constrained finite time optimal (CFTO) controller design is presented for unknown, discrete-time linear systems, whose dynamics are identified via set-membership identification (SMI) algorithms. The controller consists of two modules: a) the set membership(SM)-identifier that identifies the system's dynamics through the extended recursive least squares (eRLS) while providing the vertices of an orthotope that contains the nominal identification parameter vector, and b) the CFTO-controller; the tuning of the controller is based on a batch tuning procedure. The controller's feasible operating region remains unchanged for: a) all SM-orthotopes that are subsets of the last orthotope for which the controller's tuning was based, and b) the calculated CFTO-controller remains constant for a large period of time. In the opposite case the control partition of the controller is re-calculated (batch process) based on the current vertices of the identified SM-orthotope. Simulation results are presented that prove the efficacy and the validity of the suggested control scheme

[1]  M. Morari,et al.  An LMI approach for H ∞ analysis and control of discrete-time piecewise affine systems , 2002 .

[2]  Gustavo Belforte,et al.  Parameter estimation algorithms for a set-membership description of uncertainty , 1990, Autom..

[3]  M. Athans,et al.  Robust linear quadratic designs with real parameter uncertainty , 1994, IEEE Trans. Autom. Control..

[4]  J. R. Deller,et al.  Least-square identification with error bounds for real-time signal processing and control , 1993, Proc. IEEE.

[5]  E. Fogel System identification via membership set constraints with energy constrained noise , 1979 .

[6]  S. Yurkovich,et al.  Parameter set estimation algorithms for time-varying systems , 1997 .

[7]  Alberto Bemporad,et al.  Min-max control of constrained uncertain discrete-time linear systems , 2003, IEEE Trans. Autom. Control..

[8]  VI. Conclusions , 1971 .

[9]  Anthony Tzes,et al.  Weighted minimum uncertainty prediction control , 1996, Autom..

[10]  Alberto Bemporad,et al.  The explicit linear quadratic regulator for constrained systems , 2003, Autom..

[11]  Alberto Bemporad,et al.  Control of Constrained Uncertain Discrete-Time Linear Systems , 2001 .

[12]  K. Passino,et al.  An optimal volume ellipsoid algorithm for parameter set estimation , 1993, IEEE Trans. Autom. Control..

[13]  Mato Baotic,et al.  Multi-Parametric Toolbox (MPT) , 2004, HSCC.

[14]  A. Vicino,et al.  Sequential approximation of feasible parameter sets for identification with set membership uncertainty , 1996, IEEE Trans. Autom. Control..

[15]  Stephen P. Boyd,et al.  A Robust Control Design for FIR Plants with Parameter Set Uncertainty , 1991, 1991 American Control Conference.

[16]  Sandor M. Veres,et al.  Predictive self-tuning control by parameter bounding and worst-case design , 1993, Autom..

[17]  J. Deller Set membership identification in digital signal processing , 1989, IEEE ASSP Magazine.

[18]  Stephen P. Boyd,et al.  Set-membership identification of systems with parametric and nonparametric uncertainty , 1992 .