Convergent Estimation Mechanism Design for Nonlinear Fuzzy Systems With Faults
Abstract:
The convergent estimation for a class of nonlinear Takagi-Sugeno fuzzy systems is concerned, where time-varying process faults and input disturbances are both involved. A convergent estimation mechanism (CEM) based on a set of fuzzy iterative estimation observers is constructed for the nonlinear fuzzy system; meanwhile, the convergence of the mean sequence of estimation errors (for both states and faults) to zero (vector) is proved. However, in the existing literature, the estimation errors can only be proved to be uniformly ultimately bounded when the fault is time varying. In the design procedure, the disturbances on systems in consideration can be isolated effectively in the obtained fuzzy iterative error dynamics through introducing a suitable isolation technique. Numerical examples give the simulation results to show the effectiveness and merits of the proposed CEM.
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