A Nonlinear State Observer Design for 2-DOF Twin Rotor System Using Neural Networks

In this paper, a stable neural network based observer for twin rotor multi-input-multi-output (MIMO) system is proposed. The twin rotor MIMO system (TRMS) is a highly nonlinear system. First, a simple local state observer for TRMS is presented. The efficiency of this observer will depend on the accuracy of the model. Then, a neural network - based observer is proposed. This observer can be applied to TRMS system without any a priori knowledge about the system dynamics. A two - layer neural network is used to approximate the nonlinearities of the system. A learning rule for neural network is given which guarantee robustness of the observer. Simulation results are carried out to exemplify the performance of the proposed observers.