Neural network has good nonlinear function approximation ability. It can be widely used to identify the model of controlled plant. In this chapter, the theories of modeling uncertain plant by using two kinds of neural networks: feed-forward neural network and recurrent neural network are introduced. And two adaptive control strategies for robotic tracking control are developed. One is recurrent...

Abstract In this paper an active controller for ground vehicles stability is presented. The objective of to force the vehicle track a desired reference, ensuring safe driving conditions in case adhesion loss during hazardous maneuvers. To aim, nonlinear discrete-time inverse optimal control based on neural network identification designed, using recurrent high order (RHONN) trained by Extended K...

in this study the wavelet neural network (wnn) and artificial neural network (ann) were used to simulate barley breakage percentage in combine harvester. the models have been trained using the same data conditions. air temperature, thresher cylinder speed, distance between thresher cylinder and concave (back and forth) and the percentage of barely moisture were as the input variables. the resul...