Adaptive Neural Network Control for Helicopters in Vertical Flight

In this brief, robust adaptive neural network (NN) control is presented for helicopters in vertical flight, with dynamics in single-input-single-output (SISO) nonlinear nonaffine form. Based on the use of the implicit function theorem and the mean value theorem, we propose a constructive approach for adaptive NN control design with guaranteed stability. Considering both full-state and output feedback cases, it is shown that the output tracking error converges to a small neighborhood of the origin, while the remaining closed-loop signals remain bounded. The simulation study demonstrates the effectiveness of the proposed control.