Optimization of PID Control Parameters Based on Improved Particle Swarm Algorithm
To address the problems of slow convergence speed,low convergence accuracy and easy to fall into local optimum of traditional particle swarm algorithm,proposes a mid-pipeline particle swarm algo-rithm(MAPSO)incorporating mid-pipeline strategy,and introduces inertia weight cosine adjustment strate-gy to avoid the algorithm falling into local optimum.The method of updating the position of free particles based on the mid-drop line strategy can speed up the convergence of particles,thus enhancing the speed and accuracy of the algorithm for finding the best.The improved particle swarm algorithm is used for PID con-troller parameter optimization and compared with Ziegler-Nichols(Z-N)formula method and linear de-creasing inertia weight particle swarm optimization algorithm(MeanPSO)for experiments.
midperpendicular strategyparticle swarmfree particlesparameter optimization of PID controller
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维普
