In the dynamic potential field environment of aircraft, obstacles introduce time-varying potential field gradients during state transitions, forming chaotic attraction domains and increasing the difficulty of obstacle avoidance. Moreover, the underactuated characteristics of the aircraft result in incomplete constraints in its kinematic system, leading to chaotic behavior that causes non smooth transitions in the trajectory. Therefore, this study proposes a smooth trajectory obstacle avoidance control method for aircraft based on iterative game feedback potential field ant colony algorithm. Firstly, construct the kinematic model of the aircraft and determine its dynamic constraints; Then, identify static/dynamic obstacles, design gravitational field (target attraction) and repulsive field (obstacle repulsion) functions, construct the total potential field function of the environment, achieve dynamic balance between global target orientation and local obstacle avoidance, break through the topological limitations of chaotic attraction domain, and improve the success rate of obstacle avoidance; Finally, under the constraint of the overall potential field function of the environment, a smooth trajectory obstacle avoidance control objective function is established from three aspects: shortest path, smoothness, and safety. The potential field ant colony algorithm is used to solve the objective function. When the gradient of the potential field suddenly changes or the distribution of ant colony pheromones is uneven, the path is prone to high-frequency jitter, exacerbating the chaotic behavior of the aircraft dynamics system and affecting the smoothness of the trajectory. Therefore, this study introduces an iterative game feedback mechanism to smooth the gradient changes in the potential field, and reduces the abrupt changes in path curvature by optimizing the distribution of pheromones, suppresses the chaotic behavior of aircraft dynamics, and converges the trajectory to a stable smooth solution, obtaining the optimal trajectory of the aircraft that can meet the requirements of trajectory smoothness and obstacle avoidance control. The experimental results show that the aircraft trajectory generated by this method can maintain a safe distance from obstacles, with a 100% success rate in obstacle avoidance. The maximum smoothness of the aircraft trajectory can reach 0.95.