Neural Network Tracking Control of the 3-DOF Helicopter with Input Saturation

In this paper, an auxiliary design system is presented to handle the input saturation (IS) of the three degree-of-freedom (3-DOF) laboratory helicopter, which is an under-actuated nonlinear multiple-input multiple-output (MIMO) system and its dynamic model involves various uncertainties and strong coupling. The proposed control approach uses robust adaptive tracking control for the 3-DOF helicopter based on neural network (NN). Parametric uncertainties, unknown disturbances and input saturation are taken into consideration in the tracking control design. NN approximation, backstepping control technique and full state feedback control are investigated to tackle system uncertainties. Auxiliary design system is to analyze the effect of input saturation. Under the developed tracking control approach, semi-global uniform boundedness of all closed-loop signals is guaranteed by Lyapunov analysis. Simulation results demonstrate that the proposed tracking control design performs well in tracking and input saturation under model uncertainties and disturbances.