Research On Key Technology For Electric Dynamic Load Simulator

The electric torque load simulation system is mainly used to simulate the test load of the aircraft servo or other servo system during operation,using a motor as a loading element.It is mainly used to simulate the load under real working conditions,and used to test and verify the performance,algorithm,stability and other characteristics of the servo mechanism.Because it completes the moment load loading while following the synchronized movement of the tested mechanism,it is also called a passive servo system.The movement of the tested mechanism will cause the loading mechanism to drag backwards,and then produce excessive torque disturbance,so that the load cannot be accurately loaded.How to accurately and timely load the load spectrum under real working conditions is the main problem of the electric torque load simulation system.This article takes this as the research object to carry out research and exploration on this issue.In this paper,a permanent magnet synchronous motor(PMSM)is used as the loading mechanism,and a mathematical model including the loading system link and the position disturbance link is established,and the time domain and frequency domain characteristics of the loading link and the disturbance link are analyzed.Then,the main factors affecting the response characteristics of the system are analyzed,and the mechanism and characteristics of position disturbance are discussed,which provides a theoretical basis for subsequent research on control algorithms and control strategies.For the system modeling error of the electric torque load simulation system,refer to the linear model of the system,use the Chirp signal to excite the system and record the system output,and use the parameter identification method to correct the discrepancy between the model's nominal parameters and the actual parameters.Then the BP neural network algorithm was used for system identification to establish a nonlinear model of the load simulator.The errors of the two modeling methods are analyzed using SSE,RMSE,and R-square.The results show that the linear model error is smaller than the ANN system identification model error.Finally,the spectral distributions of the two modeling errors are analyzed using probability density and power spectral density.The results show that the errors of both models show a normal distribution characteristic,and the errors are mainly concentrated in the low-frequency region.The error characteristics are close to Gaussian colored noise.Aiming at the characteristics of coupling interference of electric load simulation system,combined with the previous analysis of the modeling error of the mechanism model,a sliding mode control strategy based on the inversion method is considered.In order to track the speed of the tested motor,a tracking differentiator based on the sigmoid function is proposed,which realizes the tracking of the speed of the tested servo.Then,based on the system characteristics of the load simulation system,system modeling errors,parameter uncertainties,non-linear links and other unknown disturbances are taken as equivalent disturbances.A second-order supers-twisting algorithm is used to estimate the equivalent interference at each step.In order to avoid the differential expansion phenomenon during the design of the inversion method,the dynamic surface is used to calculate the derivative of the virtual control variable.Finally,the effectiveness of the algorithm is verified by simulation experiments.Finally,an electric torque load simulation experimental platform was built,and the above control algorithm and control strategy were verified by verification.The experimental results show that the control algorithm proposed in this paper can better control the effect,overcome the excess torque existing in the system,and meet the evaluation index of the load simulation system.An extended application example based on electric torque load simulation system in industrial production is given at the end,indicating that the electric load simulation system has broad application prospects.