Bionic fish has broad prospect for engineering application. For the control of bionic fish, the first thing to solve is the tracking problem. However, the existing fish control methods based on CFD methods and traditional control algorithms feature high training data acquisition costs and unstable control. This study proposes an intelligent control method based on the PPO algorithm for bionic fish tracking. The surrogate model is employed instead of CFD to generate training data to improve the data generation efficiency. The efficient PPO algorithm is introduced to accelerate the learning speed of the strategy model and improve the utility of the training data. The speed parameter is introduced to solve the problem that the fish cannot track smoothly in the sharp turning area. Experiments show that the proposed method has faster convergence speed and more stable control ability in various paths, with guiding significance for the intelligent control of bionic robotic fish.