Fuzzy Scheduler Fault-Tolerant Control for Wind Energy Conversion Systems

In this paper, a new fuzzy scheduler fault-tolerant control method is proposed for nonlinear systems subject to sensor faults, parameter uncertainties, wind disturbance, and state variables unavailable for measurements. An algorithm based on the reconfiguration mechanism is then investigated for detection, isolation, and accommodation of sensor faults. The Takagi-Sugeno fuzzy model is employed to represent the nonlinear wind energy conversion system, and then a model-based fuzzy scheduler controller design uses the concept of general-distributed compensation. Sufficient stability conditions are expressed in terms of linear matrix inequalities, which can be solved very efficiently using convex optimization techniques. The proposed algorithm maximizes the produced power and minimizes the voltage ripple and is able to maintain stability of the system during sensor faults, wind disturbance, and parameter uncertainties. The design procedures are applied to a dynamics model of the typical wind energy conversion system to illustrate the effectiveness of the proposed control technique.