In a typical servo system, the control process involves several stages: acceleration, constant speed, deceleration, and low-speed approach to the target position. Throughout this entire process, the system operates under position closed-loop control. Among these stages, the deceleration and low-speed approach phases play a crucial role in determining the overall positioning accuracy. There are various methods used for deceleration control. Two common approaches are exponential law and linear law acceleration/deceleration algorithms. The exponential law algorithm is known for its strong tracking performance, which makes it ideal for applications requiring high responsiveness, such as cutting processes. However, when operating at higher speeds, it may exhibit poor stability. On the other hand, the linear law algorithm provides better stability, making it more suitable for fast positioning tasks where speed variations are significant. When choosing between these two methods, it's important to consider not only the system's stability but also the precision achieved when the system comes to a stop. Theoretically, both exponential and linear deceleration laws can achieve accurate positioning if the deceleration point is properly selected. However, determining the exact deceleration point remains a challenge. There are a few common strategies for identifying the deceleration point. One method involves using the same acceleration/deceleration profile during both start-up and stop, allowing the deceleration point to be calculated based on the symmetry and parameters of the acceleration phase. Another approach is to calculate the deceleration point using parameters such as feed speed, deceleration time, and deceleration rate. With today’s high-performance CPUs, implementing these calculations in CNC servo systems is straightforward and efficient. This makes the first method particularly flexible and widely used in practical applications.
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