To solve the problems of insufficient search power and low convergence accuracy in the optimization process of Biogeography-Based Optimization (BBO) algorithm, an Improved Migration Operator BBO (IMO-BBO) algorithm was proposed. On the basis of BBO algorithm and combining with the evolution thinking of “survival of the fittest”, the migration operator was improved by taking migration distance into consideration, and the differential strategy was used to replace individuals unsuitable to migration, so as to increase the local exploration ability of the algorithm. At the same time, the concept of multi-population was introduced to enrich the species diversity. IMO-BBO algorithm was tested on 13 benchmark functions. The results show that compared with the Covariance Matrix based Migration BBO hybrid with Differential Evolution (CMM-DE/BBO) algorithm and the original BBO algorithm, the improved algorithm enhances the search ability for global optimal solutions and simultaneously improves the convergence speed and the accuracy significantly. IMO-BBO was applied to PID parameter tuning, the results show that the controller optimized by this algorithm has faster response speed and more stabile accuracy.