Optimal fault resilient autonomous quadcopter control based on dynamic partial reconfigurable FPGA

Abstract Quadcopters are in enormous demand in mission-critical applications where there is a large risk to human life, such as border patrolling, emergency rescue, and production monitoring in chemical industries. Autonomously flying quadcopters can ensure higher levels of safety than remotely controlled quadcopters. Due to the complexity of autonomous quadcopters, there is a risk of failure, posing an enormous challenge to successful mission completion. Additionally, due to space constraints and the need for extended operation, the controller area and propulsion power are to be lower along with higher speeds of tracking for reaching the destination as early as possible. With these conflicting requirements, these metrics can be optimized in stages by reconfiguring the controllers on FPGA-based systems. Different controllers and suitable references are chosen and brought into action based on the metric that is lagging once they are found suitable to operate safely. This combination of control and reference reconfiguration and switching of main/auxiliary controllers is expected to ensure speed, area, and power optimization with improved fault resilience, ensuring better mission completion possibilities. This has been verified with Simulink-based algorithms of both continuous systems and fixed point-based digital systems and FPGA-based system co-simulation with the Simulink-based quadcopter model. Finally, the synthesis and implementation of the FPGA-based system is also taken up on Zynq Ultrascale±based devices with Vivado v2018.3-based IDE.