Plant-friendly signal generation for system identification using a modified SPSA methodology

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.