FT-BarrierCertificate

UAV Simulation of our paper 'Barrier Certificate based Safe Control for LiDAR-based Systems under Sensor Faults and Attacks'

H. Zhang, S. Cheng, L. Niu and A. Clark, "Barrier Certificate based Safe Control for LiDAR-based Systems under Sensor Faults and Attacks," 2022 IEEE 61st Conference on Decision and Control (CDC), Cancun, Mexico, 2022, pp. 2256-2263, doi: 10.1109/CDC51059.2022.9992432.

Description

This section evaluates our proposed approach on a UAV delivery system in an urban environment. The UAV system is based on MATLAB UAV Package Delivery Exampl. The UAV adopts stability, velocity and altitude control modules, rendering its position control dynamics to be:

$$\begin{equation} \begin{bmatrix} [x]_1\\\ [x]_2 \end{bmatrix}_{k+1} = \begin{bmatrix} 1 & -4.29\times 10^{-5}\\\ -1.47\times 10^{-5} & 1 \end{bmatrix} \begin{bmatrix} [x]_1\\\ [x]_2 \end{bmatrix}_{k} + \begin{bmatrix} 0.0019 & -1.93\times 10^{-5}\\\ -2.91\times 10^{-4} & 0.0028 \end{bmatrix} \begin{bmatrix} [u]_1\\\ [u]_2 \end{bmatrix}_{k}, \end{equation}$$

where $x[k]=[[x]_1,[x]_2]^T$ is the UAV position, $[x]_1$ and $[x]_2$ represent the position of UAV on $X$-axis and $Y$-axis, respectively. The UAV has one LiDAR sensor and two inertial navigation system (INS) sensors, denoted as INS1 and INS2. The UAV maintains two EKFs associated with each INS sensor to estimate its position at each time $k$, denoted as $\hat{x}_1[k]$ and $\hat{x}_2[k]$, respectively. The system operates in the presence of an adversary who can compromise one of the INS sensors and spoof the LiDAR sensor.

Fault tolerant estimation for LiDAR-based system removes conflicting state estimations by comparing estimations of proprioceptive sensors with additional information from exteroceptive sensors measurements.

Getting Started

Environment

• MATLAB 2020b
• UAV Toolbox for 2020b and its dependency

Run FT-LiDAR Estimation

• In UAV_FT-LiDAR_Est directory
• Run attack_figure.m

Run Baseline under FDI Attacks

• In UAV_Baseline directory
• Open project file uavPackageDelivery.prj
• Run file FlyFullMission.m or Click the icon indexed 6
• Run Simulation file uavPackageDelivery.slx by clicking RUN

Run FT-Barrier Certificate under FDI Attacks

• In UAV_FTBC directory
• Open project file uavPackageDelivery.prj
• Run file FlyFullMission.m or Click the icon indexed 6
• Load mapdataDemo.mat
• Run Simulation file uavPackageDelivery.slx by clicking RUN

Data and Plots in Our Paper

• In DataFigures directory
• Run CDC_figure_1.m to plot FT-LiDAR Estimation figures
• Run CDC_figure_2.m to visualize trajectories of the UAV when controlled using our proposed approach and the baseline.

Code Authors

• Hongchao Zhang, Ph.D. Candidate, [email protected],
  Electrical & System Engineering, Washington University in St. Louis

• Shiyu Cheng, Ph.D. Student, [email protected]
  Electrical & System Engineering, Washington University in St. Louis