The Research Of The Disturbance Rejection Of PMLSM

With the rapid development of the servo drive technology, high-speed and high-precision has been the inevitable tend of industrial automation. Scholars pay more attention to the permanent magnet linear synchronous motor, becaue of its superiority in structure. But the drive system, which is based on the permanent magnet linear synchronous motor, is vulnerable to end effect, cogging force, ripple disturbance and other disturbances which confine its application in high-accuracy control field. This paper chooses the disturbance rejection as research subject, designs the adptive iterative learning controller for repeat position tractk and designs Proportional-Integral-Derivative Neural Network controller and GA(Genetic Algorithm)-BP Neural Network controller for speed control to improve the performance of the drive system.Firstly, this paper introduces the structure of permanent magnet linear synchronous motor and the fundamental of vector control. This paper analyzeses the disturbances of the permanent magnet linear synchronous motor and gives the mathematical description of the disturbances. And, the complete mathematical model of permanent magnet linear synchronous motor is achieved.Secondly, this paper designs an adptive iterative learning controller for the drive system, which should have tracking ablity for a periodic trajectory and rejection ablity for a periodic disturbance. The simulations indicate that the adptive iterative learning control scheme can effectively improve the position precision.What’s more, this paper designs the PIDNN and GA-BP controller for speed control. And,this paper makes a comparison between the PIDNN algorithm and GA-BP algorithm. The simulations indicate that the PIDNN control scheme and GA-BP control scheme is more effective than PID control scheme. What’s more, the PIDNN control scheme is more effective than GA-BP control scheme.Finally,this paper sets up the experimental platform based on the controller of NI Compact RIO, which is used to test the effectiveness of the PIDNN control scheme. Compared with the normal control scheme, the PIDNN control scheme is more effective for the rejection of the periodic disturbances.and has practical value.