For intelligent mechanical systems, processing multisource sensor data is crucial for safe and robust control. While sensor fusion is typically optimized for estimation precision, its impact on closed-loop stability is often overlooked: the interplay between multisource sampling rates can introduce destabilizing disturbances. This paper analyzes the stability of a first-order system controlled via a sensor fusion-based feedback loop, with special attention to the stability properties of such systems. By investigating the sampling frequencies and time delays, we demonstrate that the update rate and controlled asynchronous sampling are critical factors of system robustness. Our results provide a theoretical basis for tuning sampling frequencies to mitigate latency-induced instability, ensuring reliable control of mechanical systems in sensor-rich environments.
