Abstract: Particle swarm optimization(PSO) has premature convergence problems.Theory and experiment prove that PSO parameters establish the proportion relation of local search capabilities to global search capabilities and have great influence to the convergence.The existing parameter adjustment strategies are studied and analyzed,and their existing problems are pointed out.Using the diversity and mutation mechanism of the vertebrate immune system for reference,a new parameter adjustment strategy is presented.The new strategy,based on the affinity of antibodies and the aggregation level of particles,determines the change rate of optimal fitness values and the value of algorithm parameters.The test results of the classic function show that the global convergence capability of the proposed method is significantly improved,and the premature convergence problem of the PSO algorithm is effectively avoided.