Abstract: The quality of control parameters of shaking table affects the precision of table waveform reproduction and the test results. In order to realize the efficient adjustment and intelligent optimization of the system control parameters, and to improve the control effect of the system, a three-parameter control parameter optimization method based on Later Random and Nonlinear Dynamic Particle Swarm Optimization (LRNDPSO) is proposed to optimize the control parameters of shaking table system.The results show that the correlation coefficient of the regenerated waveform under the optimization parameter control of the improved algorithm is more than 25% higher than that under the theoretical parameter control.Compared with the simulation results of experimental feedback data, the correlation degree of simulation waveform under the control of optimization parameters increases to more than 0.95, and the absolute peak error decreases to less than 10%. The comparison results show that the algorithm is feasible and effective, the system has better adaptability to different input waveforms under the control of optimization parameters, the system is better controlled.