Research On Motion Control Of Hydraulic Demolition Robot Working Arm

In recent years,hydraulic demolition robots have become more and more widely used in the demolition of used buildings,decontamination of nuclear energy,emergency rescue,etc.by virtue of their safe and efficient operation methods.Modern robots pay more attention to their automation and intelligence,and the key to automating them is the automation of the working arms.Firstly,the kinematics analysis of the robot working arm is carried out.The kinematics model of the working arm is established based on the D-H coordinate method.The forward and backward kinematics of the working arm are solved,and the working size of the working arm is obtained.The joint simulation analysis of the working arm is based on SolidWorks and ADAMS software,and the working range curve and end position change curve of the working arm are obtained.Comparing the two calculation results with the actual measurement data,the correctness of the theoretical model of the working arm is verified,which provides a theoretical basis for the structural optimization design and control of the working arm.Secondly,for the hydraulic control system of the working arm,the components of the electro-hydraulic proportional control system are simplified and mathematically modeled,and the transfer function of the electro-hydraulic proportional control system is obtained,and the stability of the system is verified.Aiming at the poor control effect,the PID controller conforming to this system is designed,and the PID simulation model is built based on Simulink.The simulation results show that the PID control algorithm is effective for this system but the effect is not significant enough.Finally,the control strategy of the electro-hydraulic proportional control system is studied.Based on the Lyapunov stability theorem,the th eoretical design controller is controlled according to the sliding mode,and the neural network control algorithm is combined to design the neural network sliding mode controller.Based on Simulink,two control system models are built for simulation analysis.The simulation results show that under the control of sliding mode variable structure,the tracking perform ance and response speed of the system are significantly improved.Based on Simulink,two control system models are built for simulation analysis.The simulation results show that under the control of sliding mode variabl e structure,the tracking performance and response speed of the system are significantly improved.The control performance of the neural network sliding mode control is better than that of the sliding mode control.The comparative analysis verifies that the neural network is effective and effective for the optimization of sliding mode control.