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Stability analysis of the particle dynamics in particle swarm optimizer

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3 Author(s)
V. Kadirkamanathan ; Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, UK ; K. Selvarajah ; P. J. Fleming

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.

Published in:

IEEE Transactions on Evolutionary Computation  (Volume:10 ,  Issue: 3 )