Soft Error Assessment of UAV Control Algorithms Running in Resource-Constrained Microprocessors

The landscape of Unmanned Aerial Vehicles (UAVs) or drones technology and their applications is increasingly evolving across various sectors. UAV s are subject to radiation-induced single event upset (SEUs); assessing their vulnerability is thus vital to avoid possible catastrophic events. This paper's original contribution is to assess the SEU vulnerability of four UAV control algorithms running in a resource-constrained micropro-cessor. Results suggest the PID for attitude and height control has the best relative trade-off between SEU vulnerability, memory-saving, performance, and power efficiency. Results also show that a self-tuning PID controller using fuzzy theory presented fewer silent data corruption (SDCs) than all other algorithms.