This paper solves the problem of distributed adaptive event-triggered optimal control for six-rotor unmanned aerial vehicles under compound false data injection attacks and lumped disturbances by using the adaptive dynamic programming algorithm. Two types of triggers are introduced, one for achieving intermittent communication between unmanned aerial vehicles and the other for acting on the electronic speed data transmission network of each unmanned aerial vehicle to address bandwidth limitations. Additionally, the design of all triggers takes into consideration the adverse effects of introducing the event-triggered mechanism on system performance, and all trigger mechanisms do not display Zeno phenomena. Then, to guarantee the robustness of the unmanned aerial vehicle systems, a novel performance index function that considers attack information is designed, and a distributed disturbance observer is also designed. Moreover, on account of finding the Hamilton–Jacobi–Bellman partial differential equation more efficiently, an intelligent learning control algorithm applying identifier-critic neural networks is proposed. Using the Lyapunov stability analysis method, the proposed disturbance-observer-based optimal cooperative control scheme can guarantee that all signals in the swarm systems are bounded and the consensus control objective is achieved. Finally, some relevant simulation verification diagrams are given to test the effectiveness of the designed control scheme