Switched systems provide a powerful modelling framework for representing complex physical processes governed by multiple operating modes and logical rules. This research advances the theoretical foundations and practical applications for switched systems by starting from the design of switched Control Lyapunov Functions (CLFS) to address complex cooperative objectives via Switching Model Predictive Control (SMPC) methods, both in a centralised and distributed fashion. 

In order to demonstrate the feasibility of the proposed strategies, two case studies were considered relying on two different classes of unmanned robotic vehicles, i.e, differential wheeled robots and quadrotors as ground and aerial robotic platforms, respectively. In both, the inherent challenges of multi-robot systems, such as physical constraints, collision avoidance, inter-agent communication, and scalability, were studied, defined and included in the problem formulation.

Moreover, the presence of a more complex system dynamics in the quadrotors motivated the proposal of a novel hierarchical control structure, combining the previously proposed SMPC framework in the high-level controller, while reducing the dynamics complexity by means of feedback linearization governed by a simple local controller. Simulated and experimental validation across both robotic domains demonstrated the efficacy of the proposed methods, contributing to the state-of-the-art in the field for robust and scalable autonomy in complex robotic applications.