Adaptive Control of a 3 Dof Helicopter Model Using Neural Networks (original) (raw)

A Neural Network (NN) combined with PD (proportional-derivative) controller is proposed in this paper for application in underactuated nonlinear systems. The main goal of this work is to solve the reference trajectory tracking problem of a three degrees of freedom (DOF) helicopter platform model with two control inputs obtained by EulerLagrange method. This control technique is derived from the estimate of the helicopter nonlinear function performed by the NN, combined with an outer PD tracking loop and an auxiliary signal that provides robustness in the face of unmodeled bounded disturbances, as well as unstructured unmodeled dynamics. The PD controller design is based on a LQR controller, which is designed by using the helicopter linearized model. Lyapunov second method is employed to establish stable weights adaptation laws, which are tuned on-line, and the control system stability, thereby guaranteeing small tracking errors and bounded control signals. The Lyapunov stability of ...