Real-Time Sub-Count Estimation With State Continuity for Asynchronous and Quantized Sensing

Precision motion control is often challenged by asynchronous sensor update and quantization noise, causing abrupt and untimely state variation to limit the machine precision. To provide smooth and accurate sensor interpretation, this study developed a novel event-triggered sub-count estimation method that addresses continuity on system states. By enforcing such state continuity on important properties such as position and velocity, the proposed method relaxes the requirement for accurate model as in the exiting model-based methods. Also, because it does not rely on long horizon of past measurements as the nonmodel-based methods do, it is able to adapt to abrupt reference changes much more quickly. When applying the proposed sub-count estimation method, a precision motion system can utilize the sensor reading more effectively and improve the tracking performance beyond the sensor resolution given available only quantized and asynchronous measurements.