<p>In this paper, a data-driven adaptive dynamic programming method is proposed to solve the thrust tracking control problem of a turbofan engine with unknown system dynamics. Firstly, the augmented system of the engine and the reference signal system is established. The thrust tracking problem can be transformed into an optimal control problem by this augmented system. Secondly, an augmented algebraic Riccati equation is derived under the performance index of the original dynamics, and an offline policy iteration method is design to solve the optimal thrust tracking problem. Thirdly, a new online data-driven adaptive dynamic programming method is proposed to solve the optimal thrust tracking problem when the engine dynamics is inaccessible. Finally, some numerical simulation results are given to demonstrate the effectiveness of the proposed method.</p>