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Open Access research which pushes advances in bionanotechnology

Strathprints makes available scholarly Open Access content by researchers in the Strathclyde Institute of Pharmacy & Biomedical Sciences (SIPBS) , based within the Faculty of Science.

SIPBS is a major research centre in Scotland focusing on 'new medicines', 'better medicines' and 'better use of medicines'. This includes the exploration of nanoparticles and nanomedicines within the wider research agenda of bionanotechnology, in which the tools of nanotechnology are applied to solve biological problems. At SIPBS multidisciplinary approaches are also pursued to improve bioscience understanding of novel therapeutic targets with the aim of developing therapeutic interventions and the investigation, development and manufacture of drug substances and products.

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Towards an intelligent, open and modular control architecture for automating the milling process

Rubio, Luis and Longstaff, Andrew and Fletcher, Simon and Myers, Alan (2013) Towards an intelligent, open and modular control architecture for automating the milling process. In: 2nd Annual EPSRC Manufacturing the Future Conference, 2013-09-17 - 2013-09-18, Cranfield University.

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This research work describes an intelligent, open and modular architecture for controlling the milling process. It is based on models of the milling process. The dynamic equation leads to the time-domain and the well-known stability plots. The linearization around the equilibrium point is represented by transfer functions. The fundamental idea of the control system is to work automatically, with a simple interface with the operator, based around the admissible cutting parameter space given by the well-known stability lobes. First, the optimization of a multi-objective cost function is used to obtain the cutting parameters. Secondly, the adaptive control scheme proposes different control laws working in parallel to address the non-linear and changeable milling process. Finally, the supervisory scheme manages the system so it can work automatically in between optimal working points.