The proposed mathematical research program includes applications specific to biological and industrial control that both involve research into control over shared networks.

The biological component is to understand how reflected waves may be relevant in control of cardiac output.
This problem will be tackled using a mixture of mathematical modelling of wave reflections in pulsatile
networks with approximate solutions developed by semi-analytic means and asymptotic expansions. Wave
reflections occur when the pulsatile blood flow encounters arterial bifurcations and as such carry information
about the fluid mechanical and structural status of the entire arterial tree back up to the aorta. In recent work by
the principal applicant and colleagues, the concept of `smart' baroreception was presented. There, the
sensitivity of aortic stretch receptors to change in global arterial tree characteristics was measured. The next
proposed steps are to understand how global arterial blood flow and pressure may be inferred via wave
reflections and then to build a closed-loop neural control model as a canonical demonstration of `smart'
baroreception. The biomedical importance of `smart' baroreception is that arterial wall stiffening followed by
sympathetic neural compensation may be a component in the onset of essential hypertension.

The industrial component is for analysis of predictive control of fast processes over shared networks. This
problem will involve the programming and use of a network simulator, mathematical analysis and design of
robust predictive control methods along with the simulation and testing of network protocols subject to
nonstationary communication delays. The aim is to provide remote control of manufacturing processes based
on a predictive control design that is robust with respect to communication delays coupled with a network
protocol designed to allow a controller to adequately compensate for such delays.