Modified Recurrent Fuzzy Neural Network Sliding Mode Control for Nonlinear Systems

In this study, a modified fuzzy neural network sliding mode control for a class of nonlinear systems is designed. Firstly, the considered nonlinear system is given and a global sliding mode control is proposed. Then, a modified fuzzy neural network (FNN) is constructed and utilized for estimating the uncertain function. Compared with the conventional FNN, the designed FNN can obtain a better generalization capability with two feedback loops. Moreover, the stability analysis in the Lyapunov framework is implemented to ensure the zero-error-convergence performance. To validate the control performance of the proposed scheme, active power filter is selected as the controlled plant. The simulation results demonstrate that the designed control method can achieve superior control capability.