Self-mining Technology Of Hydraulic Excavator

The main purpose of this paper is solving the problem of controlling the movement of a robotic excavator’s working device, and finding an efficient method of path planning and trajectory tracking control, so as to realize the efficient tracking to the working device’s desired trajectory.In order to deeply study this subject, the author of this paper analyse the hydraulic robotic excavator’s development and research status, and build the self-mining excavator experimental platform based on the SWE-17intelligent excavator. Specific work mainly involves the following aspects:The modeling way used to analysis the working device mechanical system of robotic excavator is applied. According to the theory about robot, the structure and operation process of robotic excavator’s working device, establish the mathematical model and simulation model about kinematics and dynamics of robotic excavator. In addition, modifies the mining resistance model based on the existing one and actual mining data of excavator, so as to analysis the external resistance on the mining process, and also provides the simulation results of dynamic.In order to revel the reason of poor motion compatibleness between joints of working device, and to provide some basis for the proposing of intelligent control algorithm, according to the characteristics of nonlinear and flow coupling for one pump two cylinders system, the hydraulic system of robotic excavator has been analysis.In order to get the optimized trajectory of working device’s joints, some kinds of optimization algorithm has been applied to solve the problems of task decomposition, path planning, and trajectory planning. At the same time, a trajectory planning software which is used to verify the effectiveness and feasibility of algorithm mentioned before has been programmed through the software of MATLAB.According to the characteristics of nonlinear and flow coupling existing on the hydraulic system of robotic excavator, a decoupling control algorithm of multivariable PID neural network that has strong decoupling ability and robustness has been adopted to overcome the nonlinear influence. At the same time, the software of MATLAB is applied to verify the effectiveness of the intelligent control algorithm.Based on the contrast experiment that the moving control of robotic excavator’s working device joints following the desired trajectory, and the analysis of experimental data, the conclusion is that the intelligent control algorithm mentioned before is feasible and effective.