Wind turbines are designed to generate electrical energy as efficiently and reliably as possible. Advanced fault detection, diagnosis, and accommodation schemes are necessary to realize the required levels of reliability and availability in modern wind turbines. This paper presents two novel approaches oriented to the design of fault-tolerant control (FTC) schemes for reliable regulation of generator torque in a wind turbine that can be affected by both model uncertainties and actuator faults in its generator/converter. The first approach is based on fuzzy model reference adaptive control in which a fuzzy inference mechanism is used for parameter adaptation without any explicit knowledge of the potential faults in the system. The second approach exploits fuzzy modeling and identification method to develop an integrated model-based fault detection and diagnosis, and automatic signal correction mechanism to accommodate potential faults in the system based on online diagnostic information. Finally, the effectiveness of the proposed FTC schemes is illustrated and compared by a series of simulations on a well-known large offshore wind turbine benchmark in the presence of wind turbulences, measurement noises, and realistic fault scenarios in the generator/converter torque actuator.
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Badihi et al. (2014) studied this question.
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