Abstract: The design of constrained, “plant-friendly ” multisine input signals that optimize a geometric discrepancy criterion arising from Weyl’s Theorem is examined in this paper. Such signals are meaningful for data-centric estimation methods, where uniform coverage of the output state-space is critical. The usefulness of this problem formulation is demonstrated by applying it to a linear example and to the nonlinear, highly interactive distillation column model developed by Weischedel and McAvoy (1980). The optimization problem includes a search for both the Fourier coefficients and phases in the multisine signal, resulting in an uniformly distributed output signal displaying a desirable balance between high and low gain directions. The solution involves very little user intervention (which enhances its practical usefulness) and has significant benefits compared to multisine signals that minimize crest factor.

AIChE shall not be responsible for statements or opinions contained in papers or printed in publications. The design of constrained, “plant-friendly ” multisine input signals that optimize a geometric discrepancy criterion arising from Weyl’s Theorem is examined in this paper. Such signals are meaningful for data-centric estimation methods, where uniform coverage of the output state-space is critical. The usefulness of this problem formulation is demonstrated by applying it to a linear example and to the nonlinear, highly interactive distillation column model developed by Weischedel and McAvoy (1980). The optimization problem includes a search for both the Fourier coefficients and phases in the multisine signal, resulting in an uniformly distributed output signal displaying a desirable balance between high and low gain directions. The solution involves very little user intervention (which enhances its practical usefulness) and has significant benefits compared to multisine signals that minimize crest factor. The effectiveness of data resulting from a Weyl criterion-based signal for Model-on-Demand Model Predictive Control (a data-centric multivariable control algorithm) is demonstrated for the distillation column case study.

Non-linear models for microwave and millimetre wave devices are commonly based on DC and S-parameter measurements, due to the absence of vectorial large-signal measurements in the past. At present, accurate prototype measurement systems are being developed, which implies that new non-linear modelling techniques can be explored. We will show experimental results of a method that allows the direct extraction of the HEMT's state-functions from vectorial large-signal measurements. I. INTRODUCTION An accurate description of the non-linear behaviour of electronic components is mandatory for adequate circuit design. A common technique to acquire the non-linear model of diodes and transistors is to make a small-signal approximation of the non-linear statefunctions at di#erent bias points #1, 2#. This technique requires a large amount of S-parameter measurements. The minimum number of required measurements can be signi#cantly reduced by extracting the statefunctions directly from large-signa...

this paper. The restoring force can be plotted in a three-dimensional graph against x(t) and x (t) . However, a more suitable representation of the restoring force can be obtained by taking the slice of this three-dimensional plot along the axes where either x(t)orx (t) equal zero. If the slice where x(t)#0(x (t)#0) is considered, the plot is called the stiffness curve #damping curve# and gives the form of the stiffness #damping# nonlinearity. Therefore, prior the identification, the RFS approach offers a very interesting way of visualizing the nonlinearity and this procedure should help to choose an appropriate model for the restoring force