Switched System

Switched systems, encompassing models where dynamics change abruptly over time, are studied to improve control and planning in complex scenarios. Current research focuses on addressing model uncertainties through techniques like Gaussian processes and developing efficient algorithms for optimal control and path planning, often leveraging structure-exploiting methods to reduce computational complexity. These advancements are crucial for applications ranging from safe autonomous vehicle navigation and adaptive cruise control to the control of multi-agent systems and robotics, enabling more robust and efficient solutions in diverse fields. The development of mode reduction techniques further enhances the practicality of these models by mitigating computational burdens associated with high-dimensional systems.