Modeling and controlling of iron and steel crane system based on improved PID algorithm
The crane is one of the most important equipment in the process of iron and steel logistics,and its operational stability and safety are crucial.Considering the impact of load swing on the driving system,the La-grange's equation was used to model the dynamics of the steel logistics driving system,the kinetic energy and the extensive force of the system were analyzed,and the simulation experiment platform of the slide rail driving was built.In response to the problem of poor control performance of traditional PID controllers in uncertain and nonlinear systems,fuzzy PID and BP neural networks were used to adaptively adjust controller parameters,im-proving the dynamic and anti-interference performance of the system.Finally,simulation experiments were conducted to compare the two improved intelligent PID control algorithms with traditional PID.Results show that both BP-PID and fuzzy PID have better performance than traditional PID,and BP-PID has the fastest re-sponse speed and robustness.
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