A comparative study is made between two global Linear Periodic Parameter-Varying (LPPV) identification algorithms. The first method is a state-of-the-art subspace identification method in the time domain. The second is a newly developed frequency domain approach, where the identification experiment is designed carefully so we can exploit the resulting structure. For both methods, the result is a state space model with an affine dependence on the varying parameters, which can be used for LPV control synthesis. Simulations show that the frequency domain procedure has a lower variance for identical experimental conditions.
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