TY - GEN

T1 - Robust experiment design for system identification via semi-infinite programming techniques

AU - Katselis, Dimitrios

AU - Rojas, Cristian R.

AU - Welsh, James S.

AU - Hjalmarsson, Hakan

N1 - Funding Information:
⋆ This work was supported by the Swedish Research Council under contract 621-2009-4017.

PY - 2012

Y1 - 2012

N2 - Robust optimal experiment design for dynamic system identification is cast as a minmax optimization problem, which is infinite-dimensional. If the input spectrum is discretized (either by considering a Riemmann approximation, or by restricting it to the span of a finite dimensional linear space), this problem falls within the class of semi-infinite convex programs. One approach to this optimization problem of infinite constraints is the so called "scenario approach", which is based on a probabilistic description of the uncertainty to deliver a finite program that attempts to approximate the optimal solution with a prescribed probability. In this paper, we propose as an alternative an exchange algorithm based on some recent advances in the field of semi-infinite programming to tackle the same problem. This method is compared with the scenario approach both from the aspects of accuracy and computational efficiency. Furthermore, the comparison includes the MATLAB semi-infinite solver fseminf to provide a general palette of methods approximating the robust optimal design problem.

AB - Robust optimal experiment design for dynamic system identification is cast as a minmax optimization problem, which is infinite-dimensional. If the input spectrum is discretized (either by considering a Riemmann approximation, or by restricting it to the span of a finite dimensional linear space), this problem falls within the class of semi-infinite convex programs. One approach to this optimization problem of infinite constraints is the so called "scenario approach", which is based on a probabilistic description of the uncertainty to deliver a finite program that attempts to approximate the optimal solution with a prescribed probability. In this paper, we propose as an alternative an exchange algorithm based on some recent advances in the field of semi-infinite programming to tackle the same problem. This method is compared with the scenario approach both from the aspects of accuracy and computational efficiency. Furthermore, the comparison includes the MATLAB semi-infinite solver fseminf to provide a general palette of methods approximating the robust optimal design problem.

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U2 - 10.3182/20120711-3-BE-2027.00346

DO - 10.3182/20120711-3-BE-2027.00346

M3 - Conference contribution

AN - SCOPUS:84867038570

SN - 9783902823069

T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)

SP - 680

EP - 685

BT - SYSID 2012 - 16th IFAC Symposium on System Identification, Final Program

PB - IFAC Secretariat

T2 - Universite Libre de Bruxelles

Y2 - 11 July 2012 through 13 July 2012

ER -