TY - GEN
T1 - Identification of externally positive systems
AU - Grussler, Christian
AU - Umenberger, Jack
AU - Manchester, Ian R.
N1 - Funding Information: The first author is a member of the LCCC Linnaeus Center and the eLLIIT Excellence Center at Lund University. He is financially supported by the Swedish Research Council through the project 621-2012-5357 and by the Swedish Foundation for Strategic Research. The remaining authors are supported by the Australian Research Council. Publisher Copyright: © 2017 IEEE.
PY - 2017/6/28
Y1 - 2017/6/28
N2 - We consider identification of externally positive linear discrete-time systems from input/output data. The proposed method is formulated as a semidefinite program, and is guaranteed to identify models that are ellipsoidal cone-invariant and, consequently, externally positive. We demonstrate empirically that this cone-invariance approach can significantly reduce the conservatism associated with methods that enforce internal positivity as a sufficient condition for external positivity.
AB - We consider identification of externally positive linear discrete-time systems from input/output data. The proposed method is formulated as a semidefinite program, and is guaranteed to identify models that are ellipsoidal cone-invariant and, consequently, externally positive. We demonstrate empirically that this cone-invariance approach can significantly reduce the conservatism associated with methods that enforce internal positivity as a sufficient condition for external positivity.
UR - https://www.scopus.com/pages/publications/85046425492
U2 - 10.1109/CDC.2017.8264646
DO - 10.1109/CDC.2017.8264646
M3 - Conference contribution
T3 - 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
SP - 6549
EP - 6554
BT - 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
T2 - 56th IEEE Annual Conference on Decision and Control, CDC 2017
Y2 - 12 December 2017 through 15 December 2017
ER -