In this paper a new approach to a neural network-based model reference adaptive intelligent controller is proposed. In this scheme, the intelligent supervisory loop is incorporated into the conventional model reference adaptive controller framework by utilizing an online growing multilayer back propagation neural network structure in parallel with it. The idea is to control the plant by convent...

Model Reference Adaptive Control (MRAC) is consists of a reference model, a plant model, and adaptive law. It is made to follow the target system to the reference model by fixed gain. As study example, Yang developed an adaptive control for SISO state space system[1]. Yang’s method[1] was not discussed about the performance of the reference model. MRAC depends on performance of the reference mo...

In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechan...

this paper introduces an indirect adaptive fuzzy sliding mode controller as a power system stabilizer for damping local and inter-area modes of oscillations of multi-machine power systems. this controller is designed based on the combination of sliding mode controller and the fuzzy logic systems. the fuzzy systems are used to approximate the unknown functions of power system model. generator sp...