Modelling and Control Approaches to System of Systems applied to Water Tank Systems and Autonomous Vehicle Platooning

The realm of control in System of Systems (SoS) is distinct from ordinary systems and covers a wide range of applications. The variance arises from the collective capabilities derived from the interconnections within the SoS, giving it a group capability beyond its components. The study of such systems can be intricate, and the challenges can vary between similar cases, necessitating distinct resolutions. Over the last two decades, researchers and industries have concentrated on the automotive sector to reduce fuel consumption, fatal collisions, and traffic congestion. A road vehicle, as a system of systems, consists of several modules that require extensive research to optimize. Approaches for controlling, predicting, and recognizing pedestrians and obstacles can vary from a simple yet effective Proportion Integral Derivative (PID) controller to data-driven methods such as Artificial Neural Networks (ANNs). Ongoing research also considers other scenarios, such as platooning in heavy-duty vehicles and urban areas. Platooning refers to a convoy of vehicles that follow the same route. They maintain proximity to reduce fuel consumption and progress as a unified unit. This is standard practice for human-driven vehicles (HDVs), and it is imperative for self-driving vehicles dedicated to logistics transportation, enabling drivers to rest and decrease travelling time. This thesis examines Systems of Systems (SoS) in various contexts, including autonomous driving systems, mathematical models, and case studies. Chapter one provides an overview of the state of the art in SoS control and the materials used in this thesis, from simulation software to hardware where the presented algorithms are implemented. Chapter two, the core of the thesis, explores the different mathematical models that can be used for the various case studies. The following section will provide a detailed explanation of each case study and its proposed solution. The case studies include a classical SoS, such as the Quadruple Water Tank Plant (QTP) control, vehicle trajectory and safety approaches, and platooning scenarios in different contexts. The final section offers insights for further research and development, highlighting potential areas for improving autonomous driving in complex scenarios.