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Novel integrated control systems together with their application within a holistic operational strategy have been created as a result of research with Caterpillar. Caterpillar the world's largest manufacturer of high-speed diesel generator sets (gen-sets) has invested [text removed for publication]. This activity yields significant commercial advantage in both performance and efficiency bringing benefits for the environment, through reduced emissions, and major customer operational savings.
Collaborations funded through EPSRC Interact and RCUK UK-China Science Bridge resulted in QUB's advanced control research having important economic and environmental impact in China, Pakistan, Vietnam. This includes the creation of new core modules for the Shanghai Automation Instrumentation Co (SAIC) SUPMAX Distributed Control System series of products now in use for whole plant monitoring and control to maximise energy efficiency and reduce pollutant emissions. These products have since 2008 increased SAIC's revenue by over $50M p.a. Related networked monitoring technologies have been successfully deployed in Baosteel's hot-rolling production lines and in the Nantong Water Treatment Company that treats 20,000 tonnes of industrial waste water daily.
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.
This case study presents the applied research work in systems modelling, control and machine vision led by Dr Haas and its impact on radiotherapy. The research is linked to a series of collaborative projects with industry and the NHS on control systems development for clinical equipment, and the evaluation of state of the art treatments. The main impacts are:
Prof Irving and Prof Sterling of the Institute of Power Systems at Brunel University collaborated with National Grid (NG) to develop and deploy a Sparse Dual Revised Simplex (SDRS), optimisation engine for real-time power allocation of all generators that were controlled by the NG. Since 2005-6 NG has been using the algorithms to aid in operation of their Balancing Mechanism, which provides a means of adjusting the level of production or consumption of individual generators or demands in the British Electricity Trading and Transmission Arrangements (BETTA). The algorithms enable the Balancing Mechanism (BM) to efficiently adjust outputs of generators in real time in order to balance the demand for electricity at minimum cost. Therefore, providing economic balancing of the transmission system at a scale of 2-3% of the £5bn annual electricity market (approximately £100M-200M per annum), hence about £800 million has been optimally traded in total in the BM since 2008. It is also important to acknowledge the reliability of the algorithms and SDRS optimisation engine from 2006 to present day, as periods of software outage carry high operational costs. The algorithms developed at Brunel continue to have very significant real world impact in terms of financial volume and its reach, such that every transmission scale power generator in the UK participates in the balancing mechanism and by implication every electricity-user benefits.
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'.
Research at the University of Strathclyde between 2003 and 2008 directly produced the following impacts from 2008 onwards: 10 wind farms (17 MW aggregate capacity) connected to the Orkney power network from 2009 to 2013 with accompanying economic and environmental benefits; Orkney power network reinforcement deferral saving of £30M from 2009 with repeat deployments of Active Network Management (ANM) technology in other UK power networks; spin-out company formed in September 2008 with total revenues to date of £6.1M, equity investment totalling £3.5M and 35 FTE jobs created; provision of new power system options for long term network plans impacting the 2013 investment decisions in distribution network companies; contribution to the emerging Smart Grid business sector in the UK and overseas from 2008.
Low-cost wireless solutions beyond the technologies available previously and developed at Loughborough University since 2005 are used by IDC, and Sure, who integrate these technologies in several products and services so generating impacts in terms of:
The technologies have been deployed in a logistics distribution centre (ToysRUs), an automotive manufacturing process (Toyota), and a safety and security system (Sure).
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%.
Research in machine virtualisation conducted in the Cambridge Computer Laboratory from 1999 onwards provides the basis for much of the present day Cloud.
Xen is a virtual machine monitor that supports execution of multiple guest operating systems consuming little overhead and providing resource isolation. This was prototyped in the Laboratory and led to XenSource, a spin-out company, which was founded in 2005. XenSource was acquired in 2007 by Citrix Systems for US$500M, and products that were launched from December 2007 onwards have had a profound impact throughout the period. Xen is now used on millions of machines around the world, providing deployment flexibility and savings on power. It forms the basis of Citrix XenServer and Amazon's Elastic Cloud 2.