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access icon free Particle swarm optimisation with Kalman correction

© The Institution of Engineering and Technology
Received 17/12/2012, Published

A novel particle swarm optimisation (PSO) method with guaranteed convergence is proposed which is useful for various optimisation problems. This proposed algorithm searches for the optimum point by the PSO algorithm and at each iteration the optimum location found so far are corrected by the Kalman correction mechanism. This global convergence Kalman PSO (GKPSO) algorithm has been tested for many benchmark problems and the results compared with another popular PSO algorithm with a neighbourhood operator. The proposed algorithm converges faster than the other and also provides better quality of solution. Convergence to the global optimum for this proposed algorithm has been proved.

Inspec keywords: Kalman filters; convergence; particle swarm optimisation

Other keywords: benchmark problems; particle swarm optimisation method; Kalman correction mechanism; neighbourhood operator; GKPSO algorithm; global optimum; global convergence Kalman PSO algorithm

Subjects: Signal processing theory; Filtering methods in signal processing; Optimisation techniques; Optimisation techniques

References

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