TY - GEN
T1 - Sensitivity-based dynamic control frequency scheduling of quadcopter MAVs
AU - Eagon, Matthew
AU - Tu, Zhan
AU - Fei, Fan
AU - Xu, Dongyan
AU - Deng, Xinyan
N1 - Publisher Copyright:
© 2019 SPIE.
PY - 2019
Y1 - 2019
N2 - Micro aerial vehicles (MAVs), in particular, quadcopters, have seen increasing adoption in many application domains due to their flexible operations and versatile functions. By taking advantages of the inherent system inertia properties of the physical platform during MAV operations, satisfactory flight performance of the vehicle can be achieved despite a variety of internal and external disturbances including environment perturbations and cyber-physical attacks, provided the fault detection and control strategy is maintained with a proper lower bound of its operating frequency. From the control design perspective, such frequency bound depends heavily on the sensitivity of the system response to its dynamic properties including inertia and dynamic couplings. For a cyber-physical system, which is subject to various cyber and physical attacks, there is usually a large sensitivity difference between physical time scale and cyber time scale. With this fact, a properly designed fault-tolerant and control strategy can leverage the inertia property of the system to arrive at an optimal control frequency to save computational power while maintaining the flight performance. For many current MAVs, their control programs are usually executed at a fixed high-frequency, which provides no significant performance gains at most of the time. In this work, we perform a sensitivity analysis and quantification of the vehicle system to guide the design and optimization of customized on-board control and computational resources. By quantifying system sensitivity and its variation across different control channels (DOFs), the computational resources can be re-distributed and optimized to detect and reject cyber-physical attacks more efficiently. With the proposed method, the cyber and physical resources of the vehicle can be allocated by system demands, which can further enhance vehicle reliability and accomplish complicated security tasks. To demonstrate the effectiveness of the proposed method, we have conducted the simulated flight test with the real vehicle parameters.
AB - Micro aerial vehicles (MAVs), in particular, quadcopters, have seen increasing adoption in many application domains due to their flexible operations and versatile functions. By taking advantages of the inherent system inertia properties of the physical platform during MAV operations, satisfactory flight performance of the vehicle can be achieved despite a variety of internal and external disturbances including environment perturbations and cyber-physical attacks, provided the fault detection and control strategy is maintained with a proper lower bound of its operating frequency. From the control design perspective, such frequency bound depends heavily on the sensitivity of the system response to its dynamic properties including inertia and dynamic couplings. For a cyber-physical system, which is subject to various cyber and physical attacks, there is usually a large sensitivity difference between physical time scale and cyber time scale. With this fact, a properly designed fault-tolerant and control strategy can leverage the inertia property of the system to arrive at an optimal control frequency to save computational power while maintaining the flight performance. For many current MAVs, their control programs are usually executed at a fixed high-frequency, which provides no significant performance gains at most of the time. In this work, we perform a sensitivity analysis and quantification of the vehicle system to guide the design and optimization of customized on-board control and computational resources. By quantifying system sensitivity and its variation across different control channels (DOFs), the computational resources can be re-distributed and optimized to detect and reject cyber-physical attacks more efficiently. With the proposed method, the cyber and physical resources of the vehicle can be allocated by system demands, which can further enhance vehicle reliability and accomplish complicated security tasks. To demonstrate the effectiveness of the proposed method, we have conducted the simulated flight test with the real vehicle parameters.
KW - CPS security
KW - Dynamic control frequency
KW - MAV
KW - Sensitivity analysis
UR - https://www.scopus.com/pages/publications/85072392100
U2 - 10.1117/12.2519105
DO - 10.1117/12.2519105
M3 - 会议稿件
AN - SCOPUS:85072392100
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Autonomous Systems
A2 - Dudzik, Michael C.
A2 - Ricklin, Jennifer C.
PB - SPIE
T2 - Autonomous Systems: Sensors, Processing, and Security for Vehicles and Infrastructure 2019
Y2 - 15 April 2019 through 16 April 2019
ER -