Abstract
This contribution deals with the state observability and parameter identifiability analysis for nonlinear wind turbine control (WTC) systems based on empirical observability Gramian (EOG) matrices. The concepts of observability and Gramian matrices are introduced to investigate the inverse condition number (ICN) and the singular value decomposition (SVD) of the EOG matrices and to evaluate different sensor configurations with respect to their degree of observability. The obtained results are then reviewed for practical plausibility over state estimates, provided by sigma-point Kalman filters (SPKF), in order to relate the observability measures directly to the expectable estimation error. The investigation reveals indeed a correlation between the employed measures for individual state observability and the estimates produced by the nonlinear filters. The joint assessment of ICN, SVD and SPKF results is found as a strong tool when aiming at a holistic and practically relevant observability discussion.
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