Neural Network Intelligent Control Based on MPSO

With the increasing complexity of mechanical equipment, control effectiveness traditional intelligent systems can no longer meet needs modern industrial production. In order to reduce errors in while ensuring system performance, this study proposes a new Particle Swarm Optimization (PSO) optimization scheme. The simplified PSO algorithm from three aspects: parameters, speed, and position formula, corrected formulas for individual optimal values global values. Research will name optimized Modified (MPSO). On basis MPSO algorithm, neural network has been innovatively improved. experimental results, controller controlled error within 0.01 0.02 seconds. At time, Whale Algorithm (WOA) was 0.072, 0.478. Compared WOA, decreased by 98.95% 93.06%, respectively. addition, proposed method not only best effect, but also shortest response with an average time 1.294 WOA optimization, it reduces 61.48% 43.07%, respectively.The results verified that effectively improve accuracy target range research simplifies calculation providing reference field control.