Repetitive Control Stores the "Previous Deviation"

In control systems, repetitive control is a method that optimizes the current control strategy by storing the "previous deviation." Its core concept utilizes historical error information to correct the current control output, thereby enhancing system stability and accuracy.

Specifically, during each control cycle, the system records the deviation between the current actual output and the desired output, storing this value in memory or a register. During the next control iteration, the system adjusts not only based on real-time feedback but also incorporates compensation from the previous deviation. This approach reduces cumulative errors and improves control precision. In code implementation, this typically involves maintaining a buffer or array to store past error values, with algorithms like shift registers or circular buffers commonly used for efficient memory management.

This method is particularly suitable for high-precision control scenarios such as industrial automation, robotic motion control, and servo systems. Its advantage lies in effectively suppressing periodic disturbances and noise, enhancing system robustness to maintain stable performance under external perturbations. Key functions in implementation often include error history tracking, compensation gain adjustment, and periodic signal synchronization mechanisms.