To reduce the impact of atmospheric turbulence on free space optical communication (FSOC) links and improve the performance of systems, an adaptive collaborative stochastic parallel gradient descent (AC-SPGD) optimization algorithm is proposed. In the iterative process of the AC-SPGD algorithm, the genetic algorithm (GA) is first used to find potential optimal parameter combinations, and then the particle swarm optimization (PSO) algorithm is used to quickly converge to the global optimal solution. Finally, the stochastic parallel gradient descent (SPGD) algorithm is used to make fine parameter adjustments, avoiding the problem of easy local extreme value convergence and slow iteration speed for SPGD. Simulation results show that the AC-SPGD algorithm can compensate for the wavefront error caused by strong turbulence in real time, achieving a good correction effect, and has faster convergence speed and higher correction accuracy than the traditional fixed gain optimization algorithm.