Adaptive Complementary Sliding Mode Control For Direct Drive Gantry Platform Servo System

In order to meet the requirements of high precision machining,the direct drive mode of linear motor has gradually replaced the driving mode of “rotary motor + ball screw”,which is widely used in gantry precision machining platform.Compared with the traditional driving method,the direct drive method can obtain better servo control performance.However,the direct drive servo system which is lack of the intermediate transmission mechanism is more likely to be affected by the nonlinear factors such as external disturbance and system parameter variation.This paper takes gantry platform for direct drive servo system as the research object,and an adaptive complementary sliding mode control method for permanent magnet linear synchronous motor(PMLSM)is proposed to reduce the influence of uncertain disturbance on the system in order to improve the position tracking and robustness of the servo control system.Moreover,in order to improve the synchronous control performance of the biaxial linear motor in the gantry platform,a synchronous controller based on Elman neural network is proposed to reduce the synchronization error of biaxial control.Firstly,the structure of the gantry platform with PMLSM direct drive control and the working principle of PMLSM are introduced.The dynamic equation of PMLSM is simplified by coordinate transformation,and the mathematical model of PMLSM is established in dq coordinate system.At the same time,according to the principle of vector control,the vector control system of PMLSM is established and the simulation model of PMLSM servo control system is established in MATLAB/Simulink.Secondly,in order to improve the robust tracking performance of single axis PMLSM servo system,an adaptive complementary sliding mode controller is designed.Complementary sliding mode control combines the integral switching surface and the complementary switching surface to limit the system state to the intersection of the two switching surface,shortening the time of the system state to the switching surface,and improving the position tracking accuracy and response time.In addition,the adaptive control law is used to estimate the boundary value of uncertainty,which can reduce the influence of uncertain disturbance on the system.The simulation results show that the proposed adaptive complementary sliding mode control method not only reduces the position tracking error under the steady state of the system,but also improves the response speed of the system.Finally,in order to improve the synchronous control performance of the biaxial linear motor in the gantry platform and reduce the synchronization error,an Elman neural network controller is proposed.Elman neural network is used to adjust the parameters dynamically and timely in order to reduce the synchronization error.The simulation results show that in different positions given,Elman neural network synchronization controller can effectively reduce the mutual influence of the uncertain disturbance on the biaxial control and reduce the synchronization error between the biaxial,and improve the synchronization and robustness of the biaxial linear motor control.