In order to realize the intelligent control of the greenhouse environment system better, aiming at the problems of non-linear, strong coupling, large lag and strong time-varying in greenhouse environment system, this paper proposes and designs a BP neural network PID controller based on genetic-particle swarm optimization on the basis of analyzing BP neural network technology.Combining the strong global search ability of genetic algorithm and the strong local search ability and fast convergence speed of particle swarm optimization algorithm, the controller optimizes the weights of neural network and effectively controls the greenhouse environment system.Finally, a comparative study of conventional and improved BP neural network PID controllers is carried out.The simulation results show that the improved BP neural network PID control has better stability and robustness.