Trucks have long been a major source of traffic problems due to their large size and weight, high risk, low speed limits, and other characteristics. Despite the development of autonomous driving control technology, the issue of truck platoon scheduling and control remains unsuccessfully resolved, and it has become even more complex with the integration of autonomous vehicles. This paper proposes a distributed model predictive control framework based on parameter-dependence Koopman operator. A three-degree-of-freedom (3-DOF) coupled vehicle dynamic model is used to capture the nonlinear dynamics of trucks. The Koopman operator is used to established linear model at different loads points based on 3-DOF dynamics and linear interpolation is applied to approximate intermediate loads. This linear parameter-dependence model is then combined with a platoon cooperative model to construct a platoon model. A distributed model controller is designed to optimizes vehicle speed, inter-vehicle spacing and track the centerline of road in real-time to ensure safe and coordinated platoon operation. The joint simulation results of Matlab/Simulink and TruckSim demonstrate that the proposed method maintains stability and safety under varying loads.