Abstract
Identification of nonlinear systems by fuzzy models has been successfully applied in many applications. Fuzzy models are capable of approximating any real continuous function to a chosen accuracy. An algorithm for real-time identification of nonlinear systems using Takagi–Sugeno's fuzzy models is presented in this paper. A Takagi–Sugeno fuzzy system is trained incrementally each time step and is used to predict one-step ahead system output. Ability of the proposed identifier to capture the nonlinear behavior of a synchronous machine is illustrated. Effectiveness of the proposed identification technique is demonstrated by simulation and experimental studies on a power system.
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