Research On The Digging Control Of The Hydraulic Excavator Working Device With Its Dynamics Analysis

Excavator is an important construction machine which is indispensable for the construction of national infrastructure.As a typical electro-hydraulic integrated equipment,its operating environment is complex and load conditions are changeable.The system modeling and effective control of its working devices have always been the focus of the industry.Due to the complex working environment of the hydraulic excavator,it is difficult to establish an accurate model of the whole excavator.In order to expand the working conditions and improve the working efficiency,the automatic control of excavator has always been a research hot spot in the engineering field.Based on the modern advanced control theory,combined with the dynamic analysis of bucket-soil interaction,sliding mode control is used in this paper to track the desired bucket tip trajectory.Firstly,kinematics and dynamics analysis of excavator working device is completed by screw theory.The forward kinematics model of excavator working device is established by using product of exponential formulas(POE).The inverse kinematics solution is decomposed into solving the known Paden-Kan Han subproblem.The differential kinematics of excavator working devic e is analyzed and the velocity jacobian matrix is obtained.Based on the screw form Kane's equation,the dynamic analysis of excavator working device is completed.Secondly,the mathematical model of excavator bucket-soil interaction is established,and the process of soil excavation is simulated under the co-simulation environment of DEM and MBD.In the mathematical model,the bucket resistance includes not only the inertia force caused by the speed change of the soil incorporated into the bucket,but also the bucket tooth resistance.In the co-simulation,the discrete element software EDEM is coupled with the multi-body dynamics analysis software Recur Dyn.The virtual prototype of excavator working device is established in Recur Dyn,the driving function is designed,and the soil particle parameters are set in EDEM,the material bed is generated,and the coupling environment is set.Finally,the coupling simulation is completed.The force curve of the bucket in co-simulation is consistent with the calculation results of the mathematical model in the stage of the increasing of the excavation depth,which verifies the correctness of the analytical mathematical model.Genetic algorithm(GA)is proposed and used to estimate soil parameters.According to the soil failure force calculated by Mohr-Coulomb soil model and Chen and Liu upper bound(CLUB)soil model,soil parameters in the mathematical analysis model of tool-soil interaction force are analyzed.The experimental data obtained from the commissioned shovel test rig are used for the estimation of soil internal friction angle,soil bulk density,soil-tool friction angle,and soil internal cohesion coefficient in genetic algorithm.With the increase of the number of constraint equations,the accuracy of soil parameter estimation is improved.Compared with Newton-Raphson method and the least square method,genetic algorithm can estimate soil parameters more accurately.According to the analysis of mathematical model,the interaction between excavator bucket and soil is affected by soil internal friction angle,bucket running speed,cutting angle,soil bulk density,adhesion coefficient and so on,it is difficult to accurately gain the dynamic resistance.Therefore,the variable structure sliding mode control is used to control the excavator bucket trajectory.And the bucket-soil interaction is introduced into the control system as an interference.In the joint space,adaptive sliding mode control is used to compensate the unmodeled dynamics and errors.Compared with the traditional sliding mode control,the adaptive sliding mode control does not need the prior knowledge of the uncertainties and reduces and eliminates the chattering phenomena.In the hydraulic driving space,the sliding mode control based on high-gain observer is designed.Based on the singular perturbation theory,the stability of the closed-loop system composed of the observer and the sliding mode controller is proved.The controller reduces the number of sensors required by the control states and the control cost.The simulation shows that by reducing the bandwidth of the observer and increasing the switching gain of the sliding mode controller,the trajectory tracking accuracy can be further improved.