Control for efficient, reliable and sustainable interconnected and intelligent autonomous systems

Project ID: 2228cd1302 (You will need this ID for your application)

Under Offer

UCL Lead department: Electronic and Electrical Engineering (EEE)

Project Summary:

Control Engineering finds broad application, developing methodologies to model, control, monitor, optimise and support decisions in a variety of systems, from single devices to increasingly complex large-scale distributed cyber-physical-human networks of systems. Applications include energy and electrical systems, transportation, smart buildings, manufacturing, water, robotics, biological systems and healthcare, addressing critical societal challenges like climate change, healthcare improvements, and the sharing economy. This project will contribute novel approaches to underlying control challenges.

Despite numerous success stories of AI and machine learning approaches in modern control systems, there have been many severe failures and issues of reliability and robustness, especially in the context of human-machine interaction. The project aims to address how control systems and AI can synergistically evolve to solve real-world engineering problems with guaranteed performance and robustness bounds in dynamic and uncertain environments. Fundamental theoretical advances will be complemented by applications studies where example domains include:

The Smart Grid concept is rapidly expanding to meet requirements for reducing carbon emissions and enhancing performance and productivity thanks to the opportunities offered by the IoT and sensing and communication technologies. Innovative control methods and architectures for the intelligent management of electrical power grid components are required to minimize capacity needs for power generation, storage, and transmission, while ensuring reliability, privacy and cyber-physical security.
Mobile robots find applications in various fields, such as autonomous vehicles and surgical robots. To fulfil the potential of these robots operating in real-world settings characterized by unpredictability and complexity, fundamental control solutions for heterogeneous robot coordination are required. Work aims to push the boundaries of robot control by enhancing their ability to adapt, react, and reconfigure at both the planning and control levels.

Self-motivated candidates who have excellent mathematical, analytical, engineering and communication skills are sought. Strengths in modelling and analysis of dynamical systems is expected.