Log in
Model Predictive Control (MPC) is a controller design methodology involving on-line dynamic optimisation of a user-defined objective. The research of Prof. D.Q. Mayne FRS and his colleagues at Imperial College has resulted in the first MPC algorithms capable of dealing with both linear and nonlinear systems and hard constraints on controls and states, thus making MPC a viable technique for industrial applications. His research in linear and nonlinear MPC has been exploited by multinational companies such as Honeywell and ABB. Evidence of impact is found in: 1) ethylene production by Basell Polyolefins GmbH resulting in economic benefits in millions of dollars annually; 2) Sinopec's JinShan power plant efficiency, reducing fuel consumptions of 500 tons of coal and 1,700 tons of coke per annum; 3) automotive powertrain design creating new business for Honeywell (based on OnRAMP design suite); 4) ABB's cpmPlus Expert Optimizer tools used for cement manufacturing, affecting companies such as Untervaz (Switzerland), Lägerdorf (Germany) and Buzzi (Italy); 5) ABB's BoilerMaz system for optimising boiler start-up mechanism resulting in energy savings per start-up of around 15%.
This case study reports the development of a new approach to solving full field reservoir problems with inhomogeneous and anisotropic permeability and variable reservoir This comprehensive body of work arose from discussions between scientists at the Schlumberger Technology Centre, Abingdon, and the internationally recognised Nonlinear Waves group in the School of Mathematics, and has been supported under two contracts with Schlumberger Oilfield UK PLC through their Technology Centre in Abingdon UK. The work has provided Schlumberger with a fast, robust and efficient tool for the rapid assessment of optimisation problems relating to oil well location sites in new oil reservoirs, and has been implemented in their recently developed GREAT facility for reservoir estimation and analysis. Schlumberger PLC is an international company which plays a premier role in supplying the petrochemical industry with services such as seismic acquisition and processing, well testing and directional drilling, flow assurance and extraction strategy. The work described in this case study took place from 2007 to 2011, and involved D J Needham (University of Birmingham) and S Langdon (University of Reading).
Research by Amol Sasane and co-authors is the foundation of an invention patented and used by the aerospace company Boeing to design flight control systems. The invention is a method which aims to optimize aerodynamic performance of aircraft, thereby improving fuel efficiency and flight safety.
Sasane and his co-authors' research is explicitly mentioned as having been used to overcome a problem in flight control — one that arises in newer, more sophisticated aircraft designs — in Patent no. US 8, 185,255 B2, 'Robust control effector allocation'.
Many operations in daily life, from manufacturing to running a hospital, need to optimise the return on use of resources where volume and value are conditions. Scheduling theory tackles some of the hardest practical optimisation problems, not known to be solvable in reasonable computation time. Strusevich and Kellerer have been able to reformulate practical scheduling challenges as `knapsack problems' - dealing with volume and value constraints - and then design approximation algorithms which can be applied back to the original challenge. The work has attracted EPSRC funding, stimulated a new field of research which is developing fast, been widely published, led to presentations at international conferences including the 2009 Computers and Industrial Engineering conference attended by industry practitioners and is impacting on Combinatorial Optimisation research.
Through close collaboration with scientists at the European Space Agency (ESA), research at the University of Southampton has developed new algorithms and an associated software tool that have contributed to more efficient spacecraft design. Now a standard component of the ESA's design technology, the tools have doubled the speed in which crucial design processes can be completed, resulting in increased efficiency over the REF period of 20 person-years — equivalent to €1 million in monetary terms — and maintaining the ESA's manufacturing competitiveness. The success of this work led to a €480,000 EU grant to adapt the tools for the avionics industry as part of efforts to meet ambitious environmental targets under the EU Clean Sky Initiative.
Professor Wright has developed practical scheduling implementations for sports fixtures and officials, with regular clients at both professional and amateur level in the UK and abroad, including the England and Wales Cricket Board and the New Zealand Rugby Union. His expertise also supports `what if' exercises, enabling clients to experiment with new ideas and announce changes with confidence that they will work in practice. His work has resulted in financial gains, substantial savings in skilled administrative time and high satisfaction for stakeholders. His research has potential reach across numerous sports, at all levels across the world.
Poor staff rosters are at the heart of socially-unacceptable working patterns, inadequate rest times and increased levels of stress. They lead to poor productivity, low levels of engagement and additional costs associated with high levels of staff turnover and absenteeism. Research undertaken at City University London has harnessed the power of `Optimisation' techniques to assist managers to draw up good quality staff rosters in hospitals, call centres and other large workforce organisations. The state-of-the-art electronic rostering programme improves use of resources, reduces reliance on costly agency staff, reduces the risk of fines for breaching legal requirements such as the European Working Time Directive and leads to significant savings in the health and social care sectors.
The application of advanced control algorithms has generated an impact on the economy and the environment through increased precision and reduced cost of operation of fast mechanical systems. A reduction in fuel consumption and CO2 emissions has been achieved in the transportation industry by the implementation of novel advanced control algorithms for advanced cruise control systems.
Work undertaken at the Applied DSP and VLSI Research Group since the early/mid nineties, has led to a number of significant contributions underpinning the development and commercial exploitation by industry of power efficient and complexity reduced integrated Digital Signal Processing (DSP) systems and products. These developments have paved the way for a new paradigm in the design of complexity reduced electronic systems aiding the emergence of numerous new commercial application areas and products in a diversity of fields. Indeed, these developments continue their currency and applicability in today's electronic products sector and thus shall be at the core of this case study.
Transport crew scheduling research at Leeds University since 1994 produced optimising algorithms and industry-ready software that led to the spinning out of Tracsis in 2004. The software, including upgrades, is used by over 40 bus and train companies who previously relied on manual processes. A minimum estimate of a £230 million saving in crew costs has been achieved in the UK alone over 2008-31.7.2013. Since 2008, the software has been routinely used by bidders in all UK rail franchise tenders, contributing to cost effective, efficient and reliable rail transport. Success led to the Tracsis floatation in November 2007 (market capitalisation: £46.7 million on 22/5/2013).