Obstacle Avoidance Control of the AGV With Actuator Dead Zones Based on Fixed-Time Disturbance Observers and Command Filtering

This study explores an obstacle avoidance control approach that takes into account both actuator dead zones and unpredictable disturbances in environments with moving obstacles. Initially, we enhance a Barrier Lyapunov Function (BLF) by introducing the concept of an equivalent safe distance. This innovation broadens the safety perimeter around obstacles by considering their velocity and movement duration, thereby simplifying the intricacies associated with moving obstacle models in avoidance strategies. Furthermore, we refine the auxiliary function within the obstacle avoidance control laws by incorporating exponential and saturation functions. This refinement ensures that as the directional error increases, the velocity of the Automated Guided Vehicle (AGV) decreases. Similarly, it guarantees a reduction in speed as the AGV nears obstacles, resulting in a smoother auxiliary function that prevents excessive speeding when approaching obstacles. Subsequently, we propose an obstacle avoidance control method for AGVs with dead zones, leveraging the enhanced BLF alongside the introduction of a fixed-time disturbance observer. This integration facilitates the estimation of disturbances within a predetermined timeframe. Unlike existing fixed-time disturbance observers, our method incorporates command filtering to mitigate the risk of computational overload. Ultimately, the efficacy of our proposed approach is validated through rigorous experimental simulations conducted on the Matlab platform.