In a linear motor, the side derived from the stator is called the primary, and the side derived from the rotor is called the secondary. In practical applications, the primary and secondary are manufactured with different lengths to ensure that the coupling between the primary and secondary remains constant within the required stroke range. Linear motors require a feedback device for linear position—a linear encoder—which can directly measure the position of the load, thereby improving the load's positional accuracy. It can be a short primary and long secondary, or a long primary and short secondary. A linear motor drive control system requires not only a high-performance linear motor but also a control system capable of meeting technical and economic requirements under safe and reliable conditions. With the development of automatic control technology and microcomputer technology, there are increasingly more control methods for linear motors.
Research on linear motor control technology can be broadly divided into three aspects:
First, traditional control technology
Second, modern control technology
Thirdly, intelligent control technology
Traditional control techniques such as PID feedback control and decoupling control are widely used in AC servo systems. PID control, in particular, incorporates information from the dynamic control process and exhibits strong robustness, making it the most fundamental control method in AC servo motor drive systems. To improve control performance, decoupling control and vector control techniques are often employed. When the object model is fixed, unchanging, and linear, and the operating conditions and environment are constant, traditional control techniques are simple and effective. However, in high-precision, micro-feeding, high-performance applications, changes in the object's structure and parameters must be considered. Various nonlinear effects, changes in the operating environment, and time-varying and uncertain factors such as environmental disturbances must be taken into account to achieve satisfactory control results. Therefore, modern control technology has attracted significant attention in the research of linear servo motor control. Commonly used control methods include adaptive control, sliding mode variable structure control, robust control, and intelligent control. These methods primarily combine fuzzy logic, neural networks, and existing mature control methods such as PID and H∞ control, leveraging their strengths and compensating for their weaknesses to achieve better control performance.
