Research On Optimization Design And Manipulator Control Of Scara Robot

With the development of robotic technology and the concept of Made in China 2025,industrial robots have become the focus in China's manufacturing industry.In the process of SCARA robot improvement,people have been pursuing the characteristics,such as high-speed,high-precision,high load-weight ratio and so on,which put forward higher requirements for the design and optimization of mechanical structures and control systems.In order to cater to the characteristics of high performance,this paper designs and manufactures a compact and lightweight SCARA robot,focuses on multi-objective optimization design for mechanical arm and in-depth study of mechanical arm control.The specific work contents are as follows:1.According to the needs of market,various solutions of mechanical transmission are analyzed and compared.selecting of key parts for robots bases on SCARA robot design target.The overall structure is established by SolidWorks,the above contents complete the compact and lightweight design.The correctness of motors and reducers are verified by ADAMS dynamic simulation.2.Finite element analysis is used to analyze the reliability by ANSYS Workbench on the worst conditions.According to dynamic and static analysis theory,optimization of facing structural dimension parameters is used to research robot body:the optimization design of arm bases on MOGA and boom bases on the combination of Topology optimization and Size optimization,which play a good role in improving the mechanical properties of large and small arms.The arms are re-modeled,and prototype is machined and debugged.3.The positive kinematics is modeled by D-H parameter method,the algebraic solution is used to solve the problem of inverse kinematics.Nonlinear dynamic model of a manipulator with joint flexibility is derived by Lagrange equation.4.Research on control of the above dynamic model bases on backstepping approach.The simulation finds that backstepping control is sensitive to the model parameters of controlled system.Therefore,neural network algorithm is introduced to design the controller,which not only solves the above problem,but also eliminates the need of accurate dynamic model.The test is simulated by the combination of ADAMS and MATLAB,the simulation results confirme the effectiveness of the proposed controlapproach,at the same time,the positioning accuracy of mechanical arm is reached according to the design target.