Research On Optimizationing Control Of The Bucket Wheel Reclaimer Based On Neural Network

Bucket wheel reclaimer are indispensable continuous material handling equipmentthermal power plants, ports, mining, metallurgy and other major industries. With the rapiddevelopment of the energy, mining, the research of the bucket wheel reclaimer automationand efficiency has become a hot topic of concern related to the field of science andtechnology workers.For bucket wheel reclaimer working environment, mechanical operation mechanismcontrol system status quo and the bucket wheel reclaimer security, stability, a controlsystem combined neural networks with PID is designed to improve the efficiency ofbucket wheel reclaimer. The main contents are as follows:Focus on the low efficiency of the reclaimer is induced by the use of separating timingcontrol in sectors of walking carts, cantilever rotation and boom elevation. The paralleloperation control mode is designed to expand the reclamier time and improve theefficiency.Further study of bucket wheel reclaimer working mode and characteristic of parallelrunning of bucket wheel reclaimer, the motion equation and the mathematical model ofsub systems are designed.Through in-depth study the nearest neighbor clustering algorithm of the RBF neuralnetwork, it is improved by K means clustering algorithm, entropy method, step length andhidden node deletion strategy etc. The improved nearest neighbor clustering algorithm cannot only simplify and optimize the network, but also can improve the learning efficiencyof RBF neural network. The improved RBF neural network PID controller is designedbased on this algorithm.In-depth study the characteristics of bucket wheel reclaimer, the control systemdiagram of bucket wheel reclaimer is designed. At the same time, the sub system of thebucket wheel reclaimer and bucket wheel reclaimer position control system arerespectively controlled by PID controller and the improved RBF neural network PIDcontroller. The MATLAB software simulation results show that this control method can not only realize the bucket wheel reclaimer decoupling control, but also can enhance theanti-interference ability of the system. Therefore, this algorithm can effectively control thebucket wheel reclaimer.