Design Of Minimum Energy Consumption Control System For Articulated Heavy-duty Handling Robot

With the continuous improvement of production technology,articulated robots have gradually replaced humans and are widely used in various industrial production fields.At the same time,it will also generate a large amount of energy consumption in actual production work.Therefore,considering the influence of factors such as non-linear friction on the energy consumption of articulated robot systems under heavy-duty handling conditions,a feasible system control strategy is proposed,and the minimum energy consumption control of articulated heavy-duty handling robots is further established.The system model to minimize the energy consumption of the joint robotic arm has become one of the key research contents in this field.The sudden acceleration phenomenon will directly affect the motion control and service life of the articulated heavy-duty handling robot.In view of the above-mentioned problems that often occur in traditional interpolation algorithms,the inverse kinematics of the robot and the five-segment S-curve are used to improve the interpolation algorithm to complete the space trajectory planning task for the articulated heavy-load handling robot model.The simulation experiments show that the proposed five-segment S-curve improved interpolation algorithm can not only complete the robot trajectory planning task,but also can better reduce the problems of joint angular acceleration mutation and large fluctuation range,so as to achieve better joint energy consumption.The articulated heavy-duty handling robot is a complex nonlinear system,which only considers the three degrees of freedom composed of the rotary axis,the boom and the small arm,and uses the Lagrange mechanics method to derive the electromechanical coupling of the articulated heavy-duty handling robot model Kinetic equations.The joint simulation platform of the electromechanical system of the articulated heavy-duty handling robot model was built,and the analysis of simulation experiments showed that the proposed torque feedforward control strategy based on the robot electromechanical coupling dynamic model can more accurately realize the movement of the robot model with a predetermined trajectory.What's more,the dynamic performance index of each motion joint is stable,and the energy dissipation is small.Based on the relevant theories and methods of optimal control,the model of the articulated manipulator drive system under load torque conditions is established,and the optimal angular velocity and control current expressions when considering nonlinear friction are derived,and the simulation experiment through real parameters.As a result,it can be seen that the total energy consumption of the joint manipulator drive system is not only affected by the load torque,but also the joule heat loss,viscous friction loss and coulomb friction loss also affect the change of the total energy consumption of the drive system.Therefore,a soft-sensing model of joint minimum energy consumption based on improved BP neural network algorithm is proposed,which can realize energy consumption prediction under unknown angular displacement and unknown load.The joint robotic motion control system experimental platform and the joint servo drive system experimental platform were built separately.The positioning accuracy test,gripping and handling physical objects and servo motor drive experiment were completed,and the HIM touch screen operation panel and lower position of the upper computer with convenient operation were designed.The PLC program of the machine realizes the communication between the configuration interface and the lower computer,and it can control the speed of the DC servo motor for joint drive.