European Research Project


Paros PLC
21 December 2007


21 December 2007
                                    ParOS plc
                                        
                           ("ParOS" or the "Company")
                                        
             ParOS delivers Advanced Controller for Batch Polymerisation
                  of Polystyrene under European Research Project

ParOS, the AIM listed advanced control company, announces that has developed a
multi-parametric model predictive controller ("m-pMPC") for the complicated
batch polymerisation of polystyrene under the European CONNECT project. ParOS
leads the CONNECT project consortium which comprises three leading research
groups, five European SME's and two large industrial companies.

As part of the project, ParOS is applying parametric Model Predictive Control
controllers in a range of different industrial scenarios. The scenarios
encompass batch polymerisation, combined heat and power production, tile
furnaces and plasma reactors for wire manufacture.

The control objective is to maintain a tight regulation of the batch reactor's
temperature profile so as to minimise the processing time and to meet tight
product quality specifications including polydispersity and molecular weight
distribution. A detailed model of the process was prepared using PSE's gPROMS
process modeling software to undertake dynamic optimisation of the temperature
profile. The model contains more than 900 variables and 30 dynamic equations.

For the design of the controller ParOS engineers created two reduced models; 
the first describes the heating start up process and the second the batch
polymerisation process. Both models are accurate enough to guarantee the
response of the controller. The controller was also designed to incorporate
disturbances and thus to eliminate the possibility of process instability and
offset.

In comparisons between the m-pMPC and a well tuned Proportional Integral
Controller the ParOS controller achieved a more accurate and faster response,
especially in the presence of unmodelled disturbances, while meeting the product
quality specifications.

Patrick McHugh, Chairman and CEO of ParOS plc, said:

"We are very pleased that ParOS can now demonstrate with its improved 
algorithms, methodologies and software tools that it can tackle some of the most
difficult control problems faced by companies in their industrial processes".


For Enquiries:

ParOS
Patrick McHugh                                             Tel: 020 3008 8223

Process Systems Enterprise Limited
Mark Matzopoulos                                           Tel: 020 8563 0888

Square1 Consulting Limited
Mike Feltham                                               Tel: 020 7929 5599



Background information on ParOS

ParOS (www.parostech.com) advanced optimisation and control solution 
technologies have been developed by a team, led by Chief Technology Officer, 
Professor Pistikopoulos, at Imperial College's Centre for Process Systems 
Engineering, over the last 15 years. ParOS became a spin-out company from 
Imperial College in January 2002 providing energy saving advanced optimisation 
and control solutions to industry. In March 2006 ParOS plc was admitted to 
trading on AIM with a view to commercialising its existing technologies and to 
utilising its intellectual property pipeline agreement with Imperial College. 
In October 2007 ParOS was formally granted European Patent EP1399784 for the 
use of its parametric Model Predictive Control ("MPC") technology.

Advanced control, referred to as MPC, is achieved by repeatedly solving 
optimisation problems online to determine the best control action, given the 
sensor measurements at any given time and a desired target value for these 
measurements. Until now providing hardware and software applications to support 
MPC has been expensive and time consuming. ParOS technology overcomes these 
obstacles using parametric optimisation techniques to determine MPC solutions 
offline that run online with low cost process controllers. ParOS' solutions are 
currently installed in the Automotive (Active Valve Train and Van Refrigeration)
and the Process (Air Separation Systems) Industries.


CONNECT project

Follow link to the official website: http://www.cpi.umist.ac.uk/CONNECT/


Background information on Process Systems Enterprise Ltd

PSE (www.psenterprise.com) is one of the world's foremost providers of Advanced
Process Modelling (APM) software to the process manufacturing industries. APM
uses high-accuracy mathematical models of process equipment and phenomena to
provide high-quality numerical information for decision support in process
innovation, design and operation. Use of PSE's technology and related
Model-Based Innovation services results in faster innovation, improved designs
of processes and products, enhancement of existing operations and more effective
R&D and experimental programmes. Results are achieved with relatively low
investment compared to alternative approaches - where these exist - with rapid
return on investment and transfer of modelling know-how to industry. PSE's
global customer base of process manufacturing companies and their technology
suppliers is served by operations in the UK, USA, Germany Japan and Korea, and
agencies in China and India. PSE is a spin-out of Imperial College London.


Background information on gPROMS

gPROMS(R) is the world's leading Advanced Process Modelling environment. It is
used to provide high-quality information for decision support in innovation,
design and operation across all sectors of the process industries, with
particular focus on modelling of complex operations such as reaction,
crystallization, polymerization and fuel cells. Companies apply gPROMS to reduce
time-to-market for new processes or products, improve designs, enhance
production, reduce capital and operating expenditure and comply more effectively
with safety, health and environmental requirements. gPROMS is applied across the
'process lifecycle', from laboratory experimentation, through process and
detailed design, to online operation, and is central to the emerging technology
of Model Based Innovation.




                      This information is provided by RNS
            The company news service from the London Stock Exchange

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