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UCL Centre for Systems Engineering

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Systems Modelling and Optimisation

System dynamic modelling, Cost-benefit analysis, Soft Systems Methodology, Intelligent systems, Adaptive modelling

A systems view of the world can be applied to good effect in most projects.

We have applied one systems thinking technique ('soft systems methodology') to help an aerospace prime contractor to learn more from its experience in previous projects. We have also used this to understand the process of discharging patients from an acute hospital.

We applied another technique ('system dynamics') to think about the implications of introducing a variable charge for household waste collection on the incidence of fly-tipping.

This is an example of a joint project we have carried out with UCL's Jill Dando Institute of Crime Science - applying systems techniques to understand the causes of crime.

We are experts in systems modelling, and are working with BAE Systems and Alexander Dennis buses on a £4m project to develop hybrid electric/diesel/fuel cell technology for passenger transit buses. The project - called Hybrid Electric Technology for Transit Buses - will last three years, and is being funded by the Government's Technology Strategy Board and the Department for Transport.

UCL's role is to perform a cost-benefit analysis of hybrid technologies relative to traditional technologies, to develop a model to optimise the energy storage and power management throughout the vehicle, and to predict the challenges of integrating the technology into the existing system.

Our Research Projects

Thesis: Robotic cites modelling methodologies for interdependent infrastructures and sociotechnical systems resilience.

Author

Yosoph Sindi

Abstract

This research is based on various century’s challenges of mass migration towards urban cities.
Many governments are heading towards the concepts of smart cities, smart ports and smart
governments as one form of coping with these challenges. The research will first demonstrate that such cities, contain inherently socio‐technically wicked problems. This research presents how important it is to take these problems into consideration when modelling such complex systems (considering minimum level of complexity). Another factor is that the socio-technical elements and cities infrastructures are interdependent. Hard systems of smart city grids and soft-systems related to services are progressing towards more autonomy requiring a new kind of intelligence. This is in need of resilience planning and with a degree of global interconnectivity. 
Due to the progress towards automation and autonomy Internet of things (IoT) is progressing towards Internet of Robotic things (IoRT). A Robotic city consists of the automated and interdependent smart-city infrastructure formed as a distributed robotic systems (mostly heterogeneous). This challenge differs from conventional robotics systems due to the involvement of socio‐technical systems, policy, complex circular lifecycle targets, IoT/IoRT, the mixed bottom-up and top-to-bottom cases. It also differs from smart city challenge due to the level of autonomy, IoRT, and socio‐technical agility. 
The proposed study methodology is to analyse sample problems that satisfy minimum level of
system complexity in a limited sample geographic area (satisfying what is commonly known as Compact Urban Centre CUC). Systems construction will be co-created with groups of stakeholders selected by the research industrial partners. The research will also investigate the difficulties in relation to urban resilience and robotic cities networks as part of a global system. 
The research modelling approach is to consider the smart city infrastructure as a heterogeneous distributed robotics system to be modelled as the individual agents in the system. The heterogeneous agents will be influenced by the inhabitants where the influence on each agent is a result or outcomes from a 4D Cellular Automata model that emulates the citizens behaviour. 
The conclusion of this research presents the effectiveness, scalability and agility of a new way to approaching such critical and complex systems.