Time-efficient structure for observer-based direct/indirect fuzzy-neural controller

This paper proposes a novel method for robust adaptive control of a class of nonlinear systems by using the proposed observer-based direct/indirect fuzzy-neural controller. Using a conventional fuzzy-neural network (FNN) encounters a seriously problem of the computation parameter explosion which leads to a huge computation time during the process of a high dimensional system. The proposed adaptive control scheme using the hybrid direct/indirect fuzzy-neural controller guarantees that the outputs of the closed-loop system asymptotically track the desired output trajectories. Finally, simulation results are presented to confirm the effectiveness and applicability of the proposed method.