Adaptive Fuzzy Identification and Control for a Class of Nonlinear Pure-Feedback MIMO Systems With Unknown Dead Zones


The adaptive fuzzy identification and control issues are considered for a category of multi-input multi-output nonlinear systems with unknown functions and unknown dead-zone inputs. The most characteristics of the thought of systems are that one) they are composed of n subsystems and every subsystem is in nested lower triangular type, a pair of) dead-zone inputs are in nonsymmetric nonlinear form, and 3) dead-zone inputs appear nonlinearly within the systems and their parameters are not needed to be known. The controller design for this category of systems could be a difficult and difficult task as a result of of the existences of unknown functions, the couplings among the nested subsystems, and therefore the dead-zone inputs. In the controller design, the fuzzy logic systems are employed to approximate the unknown functions and also the differential mean price theorem is used to separate dead-zone inputs. To catch up on dead-zone inputs, the compensative terms are designed within the controllers. The soundness of the closed-loop system is proved via the Lyapunov stability theorem. A simulation example is provided to validate the feasibility of the approach.

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