Real-time implementation of Chebyshev neural network observer for twin rotor control system

This paper addresses the problem of observer design for the twin rotor multi-input–multi-output (MIMO) system which is a nonlinear system. Exact knowledge of the dynamics of twin rotor MIMO system (TRMS) is difficult to obtain but it is highly desired that the observer can dominate the effects of unknown nonlinearities and unmodeled dynamics independently to prevent the state estimations from diverging and to get precise estimations. The unknown nonlinearities are estimated by Chebyshev neural network (CNN) whose weights are adaptively adjusted. Lyapunov theory is used to guarantee stability for state estimation and neural network weight errors. A comparative experimental study is presented to demonstrate the enhanced performance of the proposed observer.