Specify Options for Zero-Pole Truncation in Model Reducer

Frequency vector

This option allows you to specify the frequencies at which to compute and plot the frequency response of the original sparse model.

Compute zeros and poles in parallel

Use parallel computing during zero-pole computation.

When you enable this option, you can explicitly choose to scale to your preferred parallel environment. Enabling parallel computing may result in improved performance during zero-pole computation. However, even with this option disabled, the algorithm can use built-in multithreading to make best use of the local resources. For more information, see MATLAB Multicore.

This option requires a Parallel Computing Toolbox™ license.

Frequency focus

Frequency range of interest, specified as a vector of form [0,fmax]. When you specify a frequency range of focus, the algorithm computes only the poles with natural frequency in this range. For discrete-time models, the software approximates the equivalent natural frequency through Tustin transform.

Since this method computes all poles and zeros in the specified frequency range, you typically specify a low-frequency range to limit computing a large number of poles and zeros. By default, the focus is unspecified ([0 Inf]) and the algorithm computes up to MaxNumber poles and zeros.

Maximum number of poles

Maximum number of poles and zeros to compute, specified as a positive integer. This value limits the number of poles and zeros computed by the algorithm and the order of the approximation of the original sparse model.

Shift

Spectral shift, specified as a finite scalar.

The software computes poles with the natural frequency in the specified range [0,fmax] using inverse power iterations for A-sigma*E, which obtains eigenvalues closest to the shift sigma. When A is singular and sigma is zero, the algorithm fails as no inverse exists. Therefore, for sparse models with integral action (s = 0 or at z = 1 for discrete-time models), you can use this option to implicitly shift poles or zeros to the value closest to this shift value. Specify a shift value that is not equal to an existing pole or zero value of the original model.

Tolerance

Tolerance for accuracy of computed poles, specified as a positive finite scalar. This value controls the convergence of computed eigenvalues in inverse power iterations.