Title :
Stability analysis of the particle dynamics in particle swarm optimizer
Author :
Kadirkamanathan, Visakan ; Selvarajah, Kirusnapillai ; Fleming, Peter J.
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, UK
fDate :
6/1/2006 12:00:00 AM
Abstract :
Previous stability analysis of the particle swarm optimizer was restricted to the assumption that all parameters are nonrandom, in effect a deterministic particle swarm optimizer. We analyze the stability of the particle dynamics without this restrictive assumption using Lyapunov stability analysis and the concept of passive systems. Sufficient conditions for stability are derived, and an illustrative example is given. Simulation results confirm the prediction from theory that stability of the particle dynamics requires increasing the maximum value of the random parameter when the inertia factor is reduced.
Keywords :
Lyapunov methods; feedback; nonlinear control systems; particle swarm optimisation; stability; Lyapunov stability analysis; inertia factor; nonlinear feedback controlled system; particle dynamics; particle swarm optimizer; random parameter; Feedback; Genetic algorithms; Lyapunov method; Nonlinear dynamical systems; Particle swarm optimization; Predictive models; Stability analysis; Stochastic processes; Sufficient conditions; Time varying systems; Absolute stability; Lyapunov stability; circle criterion; particle swarm optimization (PSO); stability analysis;
Journal_Title :
Evolutionary Computation, IEEE Transactions on
DOI :
10.1109/TEVC.2005.857077
