Adaptive control of novel fuzzy systems with unknown parameters in membership functions

In this paper, a set of novel fuzzy-model-based adaptive control scheme is provided to further address the parameters mismatch comprised in membership functions matrices. This novel fuzzy model is proposed by Li et al. in 2015, which extended the kernel idea of Ge-Li fuzzy model to model nonlinear dynamic systems with the concepts of small-range modeling and nonlinear terms group to simplize the complicated modeling process. However, in the case of nonlinear dynamic systems with some uncertain parameters, the corresponding membership function matrices may include those uncertainties through the process of packaging the nonlinear terms groups. Consequently, in this paper, a set of fuzzy adaptive control scheme is proposed to achieve the adaptive control goal of two novel fuzzy systems with uncertain membership function matrices. Two identical complicated dynamic systems, Quantum-CNN system (Q-CNN system) with some extra added uncertain terms, are designed and illustrated for numerical simulation example to show the effectiveness and feasibility of the proposed fuzzy adaptive control scheme.