Nonlinear Flight Attitude Control Using Error Dynamics Based Dual Heuristic Dynamic Programming

This paper presents an improved approach called error dynamics based dual heuristic dynamic programming (ED-DHP) for nonlinear flight attitude control. The augmented system state containing tracking error and reference trajectory are defined for the DHP to solve the tracking problem, without requiring the complete knowledge of the vehicle dynamics and the reference trajectory dynamics. A recursive least square method is used to identify not only the input dynamics, but also the total uncertainty of the system based on the error dynamics in real time. The simulations of two different air vehicles demonstrate the good performance of ED-DHP for the online self-learning flight attitude control.