Parameter Estimation in the Nonlinear System of a Helicopter using Hopfield Neural Networks

This paper addresses the issue of using Hopfield Neural Networks for helicopter parameters estimation. A Hopfield Neural Network is an appropriate nonautonomous nonlinear dynamical system to estimate time-evolving estimate of the actual parameterization. A linearization procedure is used. Proof of convergence of the modeled parameters to their true values and boundedness of parameter estimates at each step are provided. Numerical results for parameter estimation of a complex eight-state hlicopter are presented to demonstrate the potential of Hopfield algoritehm. Linear equations of a helicopter were examined and convergence of Hopfield neural network to the linearized system parameters is addressed