To improve the performance of PSO (particle swarm optimization) optimization algorithm, a new algorithm – CPSO (chaotic particle swarm optimization)was proposed. The algorithm chaotic search mechanism〓was introduced to the particle swarm algorithm to increase the diversity of particle. In order to improve the diminishing policy flaws, the algorithm also adopts the methods of increasing particle interaction strategy and the firstincreasedthendecreased inertia weight factor model to set inertia weight factor. The improved algorithm and PID single neuron are combined, and which is used in hot rolling looper decoupling control system. Simulation results show that the algorithm can overcome the defects of PSO in prematureness and being easy to fall into local optimum. This research puts forward a new and effective way to solve the high tension coupling problem in looper system.
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周建新.基于混沌PSONN-PID神经网络的热连轧活套系统自适应解耦控制[J].机床与液压,2016,44(6):30-35. . Adaptive decoupling control for looper system of hot strip mill based on chaos PSONN- PID neural network[J]. Machine Tool & Hydraulics,2016,44(6):30-35