Systems and systems-of-systems and sub-systems are ubiquitous in both the natural and the engineered. The design and control of system behaviour is therefore a chief challenge where people, technology and the environment interact. In order to address the emergent behaviour of multiple systems, the functional and non-functional interactions between subsystems must be analysed and understood which necessarily involves modelling of the system and therefore identification and estimation of parameters. Together the members of this group aim to develop the techniques used in the modelling, analysis, design, validation and control of dynamic, multi-domain physical, and other, systems. The research spans multiple domains and incorporates the analysis of natural feedback control systems, using tools and ideas from feedback control theory with findings and strategies disseminated to designed systems and interventions in biomedicine. The aims of the theme therefore incorporate techniques and computer tools for modelling, predicting and analysing the behaviour of dynamic systems; and the techniques employed in feedback control system design and system validation.
Identification of complex engineering systems
Mathematical models of physical processes invariably include unknown parameters, which need to be estimated from real data. Theoretical techniques exist for ascertaining whether such unknown parameters can be identified from perfect (noise-free) system observations, and there is longstanding research interest in this field of identifiability analysis.
System of systems in applications to automotive vehicles
A major field of research concerns the application of systems engineering approaches in the design, development and validation of systems within automotive vehicles. Current work is focused on addressing the functional interactions between advanced powertrain and chassis systems. A major new development involves extending this work to embrace advanced electrical and electronic system architectures. One area is addressing the challenges that arise from the integration of complex, networked, in-vehicle control systems. A second involves the selection and integration of advanced powertrain architectures for hybrid/electric vehicles. This research is supported by extensive experimental facilities that include a reconfigurable hybrid/electric powertrain test facility, a LabCar and real-time hardware-in-the-loop test equipment and is carried out in close collaboration with industry.
Chaotic systems - Interplay between noise and chaos
Many low-dimensional nonlinear systems exhibit the complex behaviour known as deterministic chaos. Examples range from quantum objects via nanotubes, atomic force microscope, neurons, semiconductors, lasers, plasma, fluid dynamics and planetary motion to galactic dynamics. The interaction of the system with its environment generates dissipation and fluctuations which are unavoidable components of a chaotic motion. Interplay between fluctuations and chaos is a fundamental, unsolved problem of physics. Although chaos is observed in many engineering objects, the chaotic regime is considering as undesirable and it is avoided in systems' design. In many cases it leads to strong limitations in use of engineering systems.
|The Systems Modelling and Control group is part of the Systems and Information Stream|
Primary group members:
Dr Igor Khovanov (Leader)