This study explores the coordinated optimization of formation control for diverse multi-agent systems operating in a combined air-ground setting, involving unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). First, the dynamics models of UAVs and UGVs are established, and graph theory is employed to describe the communication topology of the system, laying a foundation for the subsequent design of control strategies. Then, based on optimal control theory, a distributed optimal formation control protocol is designed, and its stability is verified using matrix theory (such as the PBH rank criterion). To further improve the control accuracy and performance, the particle swarm optimization (PSO) algorithm is used to optimize the weight coefficients in the linear quadratic regulator (LQR) controller. Finally, PSO-LQR, LQR and adaptive control methods are used to evaluate the convergence speed of different control methods respectively in the comparison experiments. The simulation results show that the PSO-LQR control strategy not only significantly reduces the formation time of the system but also effectively accelerates its convergence speed, thereby enhancing the overall performance of the heterogeneous formation control.