Systems and Control

Works on advanced process control and monitoring, state estimation, and multivariable controller design. Ensuring stability and safety while enhancing control system performance is the driving force of the research. Applications include (but not limited to) HVAC system, distillation columns, process systems, autonomous vehicles, guidance and navigation, etc.

Works on control systems for networked and autonomous applications, spanning multi-agent systems, optimal and structured controller design, autonomous motion planning, and cyber-physical security. Recent work includes data-driven controller synthesis and the co-design of event-triggered and sparse control for resource-aware networked control systems.

Works on system and control theory, including robust and adaptive control, estimation and filtering, and machine learning for adaptive systems. Application areas span the control of photovoltaic systems and microgrids — adaptive grid synchronisation, maximum power point control, and distributed microgrid control — together with active power filtering, electric vehicles, and marine robotics including autonomous underwater vehicles.

Works on system and control theory at the intersection of engineering and mathematics, together with statistical learning theory and compressed sensing. Research has produced foundational results on how machines learn from examples, with recent work applying machine-learning methods to computational biology and the design of personalised cancer therapy.