Research On Synchronous Control Technology Of Dual-motor In Crawler Crane Lifting System

Hydraulic lifting system is a most important part of crawler crane, itssecurity, stability and handling performance is directly related to the machine'sperformance, it is also an important indicator of the performance merits of theevaluation of a crane. In order to ensure the reliability of the work, a largecrawler crane is often used single hook dual winch lifting structure consists oftwo structures, the same parameters of the hydraulic motor upgrade with ahook to complete the lifting of heavy objects. However, due to hydraulicfluctuations, the system leakage and external interference factors there areoften the synchronization error, how to ensure the synchronization controlaccuracy of the double-winch system to become the most important issuebefore the designerHowever, hydraulic synchronization control methods, most of the existingcontrol methods are often too complex or too many conditions attached, withsome targeted and significant limitations on the application. Therefore, startingfrom the simple and practical point of view, the combination of analysis andresearch work done a lot of school-enterprise cooperation project of 450tcrawler crane, the purpose of the study is to find a suitable control law,dual-motor synchronous control to obtain a higher synchronization accuracy.The main work is as follows:1. The system mathematical model based on the structure and principlesof the hydraulic lifting system and its key components in-depth study andanalysis on the dynamic characteristics of the system transfer function, find outthe impact of dual motor synchronous control The accuracy of the relevantfactors.Gradient balancing valve dynamic characteristics of the flow area for thebalance valve valve port, put forward a new kind of balance valve valve port structure to improve the valve port through flow area gradient mutations affectthe hydraulic fluctuations; taken to optimize the balance valve and motorpressure shut-off valve structure parameters and other measures to reduce thevolatility of the system pressure in order to reduce pressure fluctuations in thesynchronization control accuracy. Proved through simulation analysis andexperimental studies to optimize the design of the program is effective andfeasible.2. To seek a new type of synchronization control method is the corecontent of this article. The neural network has the accurate identification andmodeling of self-learning function, does not require the controlled object, youcan use a simple method to achieve effective control of complex systems. Thisinnovation to single-neuron intelligent control strategy applied to crawlercranes, dual hoist control system and neural network control with conventionalPID control the combination, for a single neuron PID control strategy. Neuronconnection weights to three and PID control parameters corresponding to thereal-time be adjusted to overcome the traditional PID control parameters cannot be on-line automatic tuning deficiencies, and thus adapt to the changingenvironment in the actual work process.3. Relying on self-learning neural network, adaptive function, the use ofsupervision Delta learning rule, the difference between the minimum criteria forcontinuous correction of the connection strength, so that the differencebetween the desired output and actual output and the connection weightsbetween two neurons the change is proportional to the amount of effectivelyspeed up the convergence, with a simple control and easy to implement,robust and strong, synchronized control of high precision.4. The single neuron control is to optimize the adjustment process througha non-linear adjustment of connection weights, the weights are the errorfunction corresponding to its negative gradient direction to automatically adjust.Therefore, the the generalized Lyapounoy nonlinear stability theory for stabilityanalysis of single neuron PID control system, summed up the method to improve system stability, that is, as far as possible, the learning rate to take asmall value in order to improve system stability. Using this method do not haveto solve the system of differential equations, stability of discrimination, simple,reliable.5. Cross-coupling synchronization control for crawler crane winch systemin two subsystems of the output as the feedback signal at the same time, thedifference between the two output as an additional feedback signal trackingeventually achieve the synchronization control purposes. This control methodthan the same manner as compared to the master-slave mode, with a fasterconvergence speed, and are well suited to the load changes, has a highsynchronization control accuracy.6. In order to verify the theoretical analysis of the correctness of rationality,and control strategy of the AMESim software and MATLAB / Simulink softwareco-simulation, and the traditional PID control and the single neuron PID controltwo control strategies compared and concluded a final conclusion, that thesingle neuron PID control on the control performance is much better thantraditional PID control, more intelligent. That the proposed control strategy inline with the initial design purpose, it provides a new thinking of hydraulicsynchronization control.