TY - GEN
T1 - Plant-friendly signal generation for system identification using a modified SPSA methodology
AU - Steenis, Richard
AU - Rivera, Daniel
PY - 2009
Y1 - 2009
N2 - The Simultaneous Perturbation Stochastic Approximation (SPSA) methodology and a modified SPSA version (MSPSA-K) were investigated for the generation of plant-friendly multi-sinusoidal signals. The MSPSA-K methodology principally differs from SPSA in that it perturbs the signal phase parameters in K subsets rather than simultaneously. SPSA and MSPSA-K provide a flexible, extensible computational framework to incorporate various plant-friendly performance measures into the design of an input signal for experimental design purposes in system identification. In this paper an objective function comprised of the input signal crest factor, rate of change, acceleration, and output crest factor is presented and applied to a representative case study. A detailed analysis of the tradeoffs between these various performance measures is illustrated by the choice of weighting of the objective function components. The proposed method can be applied to signals with an arbitrarily-defined spectrum (in both amplitude and frequency spacing) and is easily implemented. Index Terms - Signal Generation, Plant-Friendly, Multi-Sinusoidal Signal, System Identification, Simultaneous Perturbation Stochastic Approximation
AB - The Simultaneous Perturbation Stochastic Approximation (SPSA) methodology and a modified SPSA version (MSPSA-K) were investigated for the generation of plant-friendly multi-sinusoidal signals. The MSPSA-K methodology principally differs from SPSA in that it perturbs the signal phase parameters in K subsets rather than simultaneously. SPSA and MSPSA-K provide a flexible, extensible computational framework to incorporate various plant-friendly performance measures into the design of an input signal for experimental design purposes in system identification. In this paper an objective function comprised of the input signal crest factor, rate of change, acceleration, and output crest factor is presented and applied to a representative case study. A detailed analysis of the tradeoffs between these various performance measures is illustrated by the choice of weighting of the objective function components. The proposed method can be applied to signals with an arbitrarily-defined spectrum (in both amplitude and frequency spacing) and is easily implemented. Index Terms - Signal Generation, Plant-Friendly, Multi-Sinusoidal Signal, System Identification, Simultaneous Perturbation Stochastic Approximation
UR - http://www.scopus.com/inward/record.url?scp=77950796195&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77950796195&partnerID=8YFLogxK
U2 - 10.1109/CDC.2009.5400015
DO - 10.1109/CDC.2009.5400015
M3 - Conference contribution
AN - SCOPUS:77950796195
SN - 9781424438716
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 470
EP - 475
BT - Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Y2 - 15 December 2009 through 18 December 2009
ER -