Abstract: Most of dynamic optimizations in chemical industry are complicated and difficult to solve.Particle swarm optimization algorithm (PSO) has been developed recently, which is suitable for solving continuous problem, but its lack of ergodicity impairs the algorithm global search property.In this paper, PSO was improved by introducing chaos to the algorithm.Taking advantage of chaos’s ergodicity, PSO could comprehensively get the useful information about the objective function, which was reflected in the present global optimal point and the optimal point of each of particle in each iteration.By this, PSO could more effectively adjust search direction of each particle and finally get the global optimal point of the problem.Experimental results showed that the proposed method was successful.The algorithm was applied to dynamic optimization of the feed-rate of a Park-Ramirez bioreactor and satisfying results were obtained.