Application of improved SA-PSO in the system error registration

System error is change in some fusion system. In order to resolve the problem of system error registration, this paper combine improved Particle Swarm Optimization (PSO) with Simulated Annealing (SA). This method integrates the capacity of fast optimization seeking in improved PSO with the characteristic of probabilistic leap in S A, which not only solves the defect that PSO easily plunges into local optimum, but also ensures population variety and avoids population degradation. The simulations show that compared with PSO and GA, improved SA-PSO has better precision in system error registration.