Robust Speed and Spacing Control Framework for Autonomous Vehicles via µ-synthesis with Descriptor Form Representation

Vehicle-following control systems represent the key autonomous driving technology, which can enhance the road utilization and relieve traffic congestion effectively. However, their stability is severely challenged by random disturbances in the external environment, parameter perturbations to their dynamic models, and the combinations of these effects. In the most adverse scenario, these effects can cause fatal traffic accidents. Therefore, focusing on the vehicle-following system design, the µ-synthesis robust control framework is proposed in this paper for autonomous vehicles to realize its speed- and spacing- tracking control that can adapt to uncertainty. The contributions of this paper are threefold: First of all, the external disturbance affecting the longitudinal motion of the vehicle is regarded as an uncertain parameter and incorporated as a variable in the dynamic control model. This effectively reduces the complexity of the control system and improves the real-time performance of the controller. Then, the state-space model of the vehicle-following system is reformulated using the descriptor form to achieve decoupled robust control of autonomous vehicles with multiple uncertain parameters. This can reduce the conservativeness of the controller. Last, with consideration of the nominal performance and robust stability, a µ-synthesis robust controller for the speed- and spacing-tracking by a vehicle-following system is developed. Experiments using the hardware-in-the-loop system are conducted to verify the effectiveness of the proposed contol framework. The results show that it has good tracking performance and is robust to parameter perturbations.