Robust H∞ Network Observer-Based Attack-Tolerant Path Tracking Control of Autonomous Ground Vehicle

Abstract:

This study proposes a robust H∞ network observer-based attack-tolerant path tracking control design for autonomous ground vehicles (AGVs) under external disturbance, measurement noise, and actuator/sensor attack signals. First, a more practical AGV system describes the longitudinal, lateral, and yaw rate interactions.

Based on Controller Area Network (CAN), local AGV information is wirelessly transmitted to remote control center to calculate control command. Two novel smoothed signal models are embedded with the AGV dynamics system as an augmented system to avoid insecure CAN corruption of actuator/sensor attack signals.

The conventional Luenberger-type observer of the augmented system can estimate these attack signals and the AGV system state simultaneously. Using estimated state and attack signals, a robust H∞ network observer-based attack-tolerant path tracking controller is created to reduce the effect of unknown disturbance on path tracking error energy and eliminate attack signals.

The robust H∞ network observer-based attack-tolerant path tracking control design for AGV is derived from nonlinear difference inequalities using convex Lyapunov function. Takagi-Sugeno fuzzy interpolation is used to approximate the nonlinear AGV system, simplifying the design to a set of LMIs that can be solved using LMI TOOLBOX in MATLAB. AGV double lane change tasks in CAN are simulated to demonstrate the design process and compare the proposed design method to the conventional steering control method.

Keywords : Remote Control, Wireless Communication, Observers, Interpolation, Delays, Control Design, Wheels, Actuators, Automatic Guided Vehicles, Control System Synthesis, Controller Area Networks, Fuzzy Control, Interpolation, Linear Matrix Inequalities, Lyapunov Methods, Mobile Robots, Nonlinear Control Systems, Observers, Position Control, Robust Control, Steering Systems, Tracking, Vehicle Dynamics

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