  As Floating Offshore Wind Turbines (FOWTs) operate in deep waters and are
subjected to stressful wind and wave induced loads, they are more prone than
onshore counterparts to experience faults and failure. In particular, the pitch
system may experience Pitch Actuator Stuck (PAS) type of faults, which will
result in a complete loss of control authority. In this paper, a novel fast and
adaptive solution is developed by integrating a model-based Fault Diagnosis
(FD) scheme and the Subspace Predictive Repetitive Control (SPRC). The FD role
is to quickly detect and isolate the failed pitch actuator. Based on the fault
isolation results, a pre-tuned adaptive SPRC is switched online in place of the
existing one, whose initial values of the parameters has been tuned offline to
match the specific faulty case. After that, SPRC employs subspace
identification to continuously identify a linear model of the wind turbine over
a moving time window, and thereby formulate an adaptive control law to
alleviate the PAS-induced loads. Results show that the developed architecture
allows to achieve a considerable reduction of the PAS-induced blade loads. More
importantly, the time needed to reduce the PAS-induced loads are significantly
shortened, thus avoiding further damage to other components during the adaption
time and allowing continued power generation.
