PSO is a stochastic optimization technique inspired by
the social behavior of bird flocking or fish schooling
(Kennedy and Eberhart, 1995). Unlike genetic algorithm
(GA), PSO has no evolution operators such as
crossover and mutation, which makes it simpler, easily
completed and fewer parameters are needed. In
response, PSO has been given extensive attention in
the vibration control field (Chia and Chia, 2008;
Chen et al., 2009; Abe, 2011).
The implementation of the PSO based on a state
machine (SM) is outlined in Figure 2.
The arrow leading from one state to another is called
a transition, and describes how the SM transits from
one state to another state. The label for the transition