UAV-assisted communication has broad application prospects in future wireless communications. Deploying it in wireless powered communication networks enables energy transmission and information collection for nodes. This paper introduces a magnetic coupling resonant wireless power transfer method based on the parity-time symmetry principle, and adopts a dual-UAV cooperative energy supply communication system. With the goal of maximizing the minimum sum rate, the trajectory of the information-collecting UAV and the power allocation of nodes are jointly optimized. Since this problem is non-convex, it is solved by methods such as the block coordinate descent algorithm, weighted minimum mean square error algorithm, and successive convex optimization. The power-transfer UAV uses a dynamic programming algorithm to select the shortest path traversing all nodes. Simulation results show that the proposed joint optimization algorithm has good convergence. Compared with the trajectory planning scheme, the minimum sum rate is improved by more than 2 times; compared with the straight-line flight scheme, the minimum sum rate is increased by about 10.7% and 4.2% under different cycles, respectively; compared with the radio frequency power transfer scheme, the minimum sum rate is improved by more than 7 times. These results verify the applicability of the proposed scheme in UAV-assisted wireless energy supply communication networks.