Vishal Vishnoi (Department of Electrical Engineering, Gujrat Technological University) discusses designing and optimization of the controller parameters for continuous stirred tank reactor systems using particle swarm optimization. The paper can be downloaded here. The author mentions the sequential parameter optimization in the following context:
“[PSO] … is motivated by the observation of social interaction and animal behaviors such as fish schooling and bird flocking. It mimics the way they find food by the cooperation and competition among the entire population . A swarm consists of individuals, called particles, each of which represents a different possible set of the unknown parameters to be optimized. The swarm is initialized with a population of random solutions .
The goal is to efficiently search the solution space by swarming the particles towards the best fitting solution encountered in previous iterations with the intention of encountering better solutions through the course of the process and eventually converging on a single minimum or maximum solution .”
 Thomas Beielstein , K.E. Parsopoulos and Michael N. Vrahatis, Tuning PSO Parameters Through Sensitivity Analysis, Technical Report of the Collaborative Research Center 531 Computational Intelligence CI– 124/02,University of Dortmund, January (2002).
 Y Zheng, Liyan Zhang, Jixin Qian Longhua Ma “Robust PID Controller Design using PSO” International Symposium on Intelligent Control IEEE Oct (2003).
 T.Bartz–Beielstein K.E. Parsopoulos and M.N. Vrahatis, “Analysis of Particle Swarm Optimization Using Computational Statistics”, International conference on numerical analysis and applied mathematics ICNAAM- (2004).