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Y. Shi and R. Eberhart, “Empirical Study of Particle Swarm Optimization,” International Conference on Evolutionary Computation, IEEE Service Center Press, Washington DC, 1999, pp. 1945-1950.

has been cited by the following article:

• TITLE: Dynamical Adaptive Particle Swarm Algorithm and Its Application to Optimization of PID Parameters

  AUTHORS: Jimin Li, Guolin Yu

  KEYWORDS: Particle Swarm Optimization; Dynamical Adaptive; PID Automatic Regulation System

  JOURNAL NAME: American Journal of Operations Research, Vol.2 No.3, September 19, 2012

  ABSTRACT: Based on a new adaptive Particle Swarm Optimization algorithm with dynamically changing inertia weight (DAPSO), It is used to optimize parameters in PID controller. Compared to conventional PID methods, the simulation shows that this new method makes the optimization perfectly and convergence quickly.