Research On Optimization Design Of Industrial Robot Servo System And Ripple Reduction Method

With the continuous increase of labor costs in recent years,industrial robots have been widely used in the fields of consumer electronics industry,automotive industry,etc.The number of new domestic industrial robots in 2018 has exceeded one third of the total industrial robots.As the core component of industrial robots,the servo system accounts for more than 20%of the total cost of the robot.Its performance directly determines the performance level of the industrial robot.At present,the market for domestic industrial robot servo systems is mainly occupied by foreign companies such as Yamaha,Matsushita and Yaskawa,and one of the main reasons is that the performance and level of domestic servo systems need to be further improved.Therefore,the servo system pulsation suppression and servo system optimization design are studied in this thesis.The specific work is as follows:For the problem of ripple of the servo system,the vector control algorithm and the feedforward decoupling algorithm are firstly used to achieve the fully decoupling closedloop control of the permanent magnet synchronous motor in this thesis.Then,based on the iterative learning control algorithm,an error compensation iterative learning control algorithm is proposed,which can be realized by adding additional controllers on the basis of the original closed loop.The combination of the algorithm and the internal model control algorithm not only achieves the suppression of the pulsation but also improves the robustness of the control system.Finally,the effectiveness of the error compensation iterative learning control algorithm is verified by simulation.For the problem of optimization design of the servo system,due to the influence of the parameters of the reducer on the performance of the servo system and the fact that the reducer accounts for the highest proportion of the cost of industrial robots,a cost-based discrete optimization design method based on the discrete optimization design method is proposed in this thesis.The optimization design method firstly determines the range of servo system components that can be selected according to the target parameter conditions,and then the inertia matching optimization method is used to gradually optimize the servo system components in the range,thereby achieving the high performance and high cost performance of the servo system.Finally,this method is used to optimize the design of the servo system for a variety of loads,the feasibility of the method is proved.In this thesis,the pulsation suppression method of the servo system is studied and an error compensation iterative learning control algorithm is proposed,which can suppress the speed ripple and torque ripple amplitude up to 55%and 25%respectively.A cost-based discrete optimization design method was proposed to optimize the servo system for various types of loads.These two methods respectively achieve the improvement of the performance of the servo system from the perspective of the optimization of the servo system control system and the optimization of the matching between the components of the servo system.