Abstract： Aimed at the multi-objective and dynamic optimization problem of satellite structure, a method called MOPSO was proposed. A strategy of decreasing the inertia weight was utilized, the particles that violated the constraints were punished respectively, and the mutation operator was introduced to enhance the diversity of swarms, giving this algorithm a better capability of global optimization. Combined with the support vector machine, MOPSO was applied to solve the multiobjective optimization problem of satellite structural dynamics. This approach obtained relatively better results compared with the results obtained by using the NSGA-II algorithm. Numerical results show that MOPSO can effectively and efficiently search and converge to the Pareto optimal front, which is dispersed and uniform.