Fuzzy on-line identification of SISO nonlinear systems
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. (C) 1999 Elsevier Science B.V. All rights reserved.
on-line identification fuzzy model gradient descent algorithm