Trajectory tracking of hydraulic excavators considering the multijoint time delay
To reduce the influence of the time-delay characteristics of the multijoint system on the trajectory tracking accuracy of the working device on a hydraulic excavator,an architecture for long-short-term memory-generalized re-gression neural networks considering time delays(TD-GR-LSTM)and a multijoint control system based on this net-work model are presented.First,the motion states of the closed chain by the geometric method are analyzed,and the inverse kinematics solution of the working device is established with a closed chain that uses the rocker arm joint as the end feedback joint.The trajectory of joint space is generated by the 4-3-3-3-4 polynomial trajectory plan-ning algorithm.Next,combining with the timing processing ability of LSTM and the strong nonlinear mapping abili-ty of GRNN and taking the target rotation angle and each delay of the proportional valve signal and joint rotation an-gle as the network input characteristics,the mapping relationship between output signals and input characteristics is established through multijoint coordinated identification.Then,the multijoint model is used as the inverse controller to realize multijoint trajectory tracking.Finally,AMESim-Simulink cosimulation on a medium excavator shows that under the no-load or variable load of different frequencies,compared with the LSTM control system not considering time delay,the developed multijoint control system considering time delays can track the planned trajectory faster and more accurately and smoothly,with smaller tracking error and strong robustness.
hydraulic excavatortime delaytrajectory trackinginverse kinematics solutionneural networkmul-tijoint control system
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维普
