A Neural Network Adaptive Trajectory Tracking Control Method for Permanent Magnet Synchronous Linear Motor

Abstract

The invention discloses a neural network adaptive trajectory tracking control method for a permanent magnet synchronous linear motor and belongs to the field of linear motor motion control technologies. The method utilizes the nonlinear mapping capability of a neural network controller to establish model estimation and compensation links of the permanent magnet synchronous linear motor, so that good trajectory tracking performance of the motor is realized. The control method comprises two parts including a neural network controller based on a radial basis function (RBF) and a robust controller with feedback gain used for carrying out model estimation and compensation and restraining the influence of a model error respectively. According to the method, the nonlinear approximation characteristic of the neural network is utilized to establish the nonlinear compensation link of the model of the permanent magnet synchronous linear motor, so that the influence of nonlinear factors, such as dead zone and thrust ripple, in a motor operation process are effectively overcome, the method has stronger anti-interference capability and good stability, and the good trajectory tracking performance can be realized.

Description

technical field [0001] The invention relates to a motion control method for a linear motor, in particular to a neural network adaptive trajectory tracking control method for a permanent magnet synchronous linear motor. Background technique [0002] Compared with the traditional rotating motor, the permanent magnet synchronous linear motor has the characteristics of simple structure and can directly drive the load without a transmission device, which eliminates the influence of gaps, dead zones, flexibility and other problems caused by unnecessary mechanical transmission links. It can realize high-speed and high-precision linear motion, so it has been widely used in the field of precision manufacturing and processing in recent years. However, in actual industrial applications, there are uncertainties and disturbances that are difficult to ignore, such as disturbances caused by load changes, uncertainties in motor parameters, friction of linear guides, and uneven magnetic fiel...

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Problems solved by technology

[0004] Generally speaking, in the actual application of the linear motor motion control system, due to the influence of uncertainty and measurement noise, it is difficult to guarantee a completely accurate estimation of the model. In order to maintain the stability of the system under the influence of modeling errors, It is also necessary to add a reasonable robust control term to the control law

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