ADAPTIVE NEURAL NETWORK CONTROL OF A LINE-OF-SIGHT SYSTEM

摘要

An adaptive neural network full-state feedback controller has been designed and applied to the passive line-of-sight (LOS) stabilization system. Model reference adaptive control (MRAC) is well established for linear systems. However, this method cannot be utilized directly since the LOS system is nonlinear in nature. Because of the universal approximation property of neural networks (NN), an adaptive NN controller is presented by generalizing the model reference adaptive control is presented by generalizing the model reference adaptive control technique, in which the gains of the controller are approximated by NNs. This removes teh requirement of linearizing the dynamics of the system, and the stability properties of the closed-loop system can be proven.