Approximation and control of systems using a neural net

The use of multilayer neural networks for approximating linear and nonlinear systems is demonstrated. The gradient method is discussed in detail. Single-input/single-output and double-input/single-output systems are considered, and gradient (backpropagation) methods are used to adjust the parameters of a three-layer neural network in order to optimize a performance function. The results of simulations for the above systems are analyzed, and appropriate graphs that verify the theoretical results are included. The approach is also used for approximating the optimal control of vibrating beams.