Robust Nonlinear Control Of Multi-DOF Micro-Dynamic Parallel Robot

The parallel robot mechanism has been in existence since 1930 s,and has been developed for several decades.Its characteristics such as strong weighing capacity,large rigidity,and good dynamic characteristics have gradually expanded the application field.In different fields of use,parallel robots have different driving methods and materials.Micro-motion parallel robot is a typical structure of micro-motion robot.Its theoretical analysis and practical research have gradually become a hot topic in the robot field.The development of parallel robot technology is extremely rapid and the corresponding applications are extremely wide.However,whether it is a general large-scale parallel robot or a micro-motion-type parallel robot,it has always faced some problems,such as the multiple solutions of the positive kinematics solution.Certainty,the singularity of the work space,etc.,make the parallel robot unable to fully exert the performance advantage of the parallel robot,and also hinder the promotion of the parallel robot.At the beginning of this article,the history of parallel robots was briefly described,and during the development process,some scholars made great contributions to certain problems.At the beginning of the article,the development status of parallel robots at home and abroad was briefly introduced,as well as the future development direction.In this paper,a 6-DOF parallel robot is taken as the research object,and robust nonlinear control is studied.First,this paper use Cartesian coordinates to construct a space describing a parallel robot whose workspace can be represented by position vectors.Based on the structural dimensions of the parallel robot,the geometric relationship is written,the transition matrix is established,and the coordinate on the movable table is transformed into the coordinate system of the fixed table.The kinematics equation was deduced using the space distance formula,and the differential method was introduced.The inverse solution equation was obtained.Afterwards,a generalized coordinate vector is chosen to express the position and attitude of the parallel robot,and the mathematical model of the parallel robot is deduced using the Lagrange equation method.However,in the modeling process,due to the fact that some dynamic characteristics in the system are difficult to compensate and the obtained model is inaccurate,this paper briefly describes the effect of uncertainty and the uncertainties that may appear in the robot system.In order to compensate effect of the uncertainties,robust nonlinear control is attempted in this paper,which is a common method for uncertainty.In order to better compensate effect of the uncertainties and exert the performance and quality of parallel robots,based on the robust nonlinear control,the neural network was introduced to identify the uncertainties and enhance the robustness of the system.At the end of the article,this project uses Solidworks software to build a 3D physical model of parallel robots,which is imported into MATLAB,and the corresponding modules are added to build the simulation system.In the spirit of practice,this paper conducted a series of experiments using the parallel robotic equipment of the laboratory and programmed the upper computer program in the Visual C++ environment.