Research On Telescopic Boom With Single Pinning System Based On RBF PID Control

Telescopic Boom with Single Pinning technique,as a key component of all-terrain crane where the key technology for its control, determines the lifting performance of the machine to a large extent. With the trend of intelligent and large-sized on crane, controlled objects have more and more obvious signs like serious nonlinear,more time-varying parameters, large-scale time-varying, demanding accuracy and so on,the conventional digital PID control technology cannot deal with such issues well. As for a controlled object, RBF neural network based PID control can simulate it by identifying its dynamic characteristics, and tune PID parameters online according to its motion law, in this way RBF based PID control can give a satisfactory solution to the above problems,with this method can obtain excellent control quality.This thesis is based on the project of TZM500all-terrain crane developed by Dalian University of Technology and TAIYUAN HEAVY INDUSTRY CO., LTD. Author dose comparative study of controlling means on telescopic boom with single pinning technique,the main work is summarized as follows.(1)Summarize the main types of telescopic boom structure at home and abroad, and to analyze the respective operating principle. Design the electro-hydraulic control system of telescopic boom with single pinning technique combined with the characteristics of all-terrain cranes, and make outsourcing parts selection.(2) Build elescopic boom hydraulic system model in AMESim and add AMESim/Simulink interface as preparation for the following co-simulation.(3) Analyse the simulation result indicators of conventional incremental PID control, BP neural network based PID control and RBF neural network based PID control,then build RBF neural network based PID controller model in Matlab/Simulink.(4) Call AMESim model in the form of S-function intoMatlab/Simulink model,then run the co-simulation to verify the control effect of the controller, analyze the results at last.In this thesis, Author designed RBF neural network based PID controller model, and applied it to the control of the telescopic boom hydraulic model,the results show that the RBF network tuning PID control has outstanding results.This method enhances the quality of telescopic boom with single pinning technique control.