Fuzzy on-line identification of SISO nonlinear systems

Abstract A new fuzzy on-line identification algorithm for a single input/single output continuous-time nonlinear dynamic system is presented. This method combines the conventional on-line identification with fuzzy logic system. The nonlinear system is approximated by a set of fuzzy rules that describe the local linear dynamic in each subspace formed by fuzzifying the input and output space. The continuous-time fuzzy input–output model is identified on-line by using the input and output measurements. A fuzzy identification algorithm has been developed and a convergence analysis is carried out. Simulation studies have demonstrated that this fuzzy on-line identifier can match the time-varying nonlinear system within ±5% accuracy.

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