Nonlinear controller synthesis for complex chemical and biochemical reaction systems

The present research study is comprised of two main parts. The first part aims at the development of a systematic system-theoretic framework that allows the derivation of optimal chemotherapy protocols for HIV patients. The proposed framework is conceptually aligned with a notion of continuous-time model predictive control of nonlinear dynamical systems, and results in an optimal way to control viral replication, while maintaining low antiretroviral drug toxicity levels. This study is particularly important because it naturally integrates powerful system-theoretic techniques into a clinically challenging problem with worldwide implications, namely the one of developing chemotherapy patterns for HIV patients that are effective and do not induce adverse side-effects. The second part introduces a new digital controller design methodology for nonlinear (bio)chemical processes, that reflects contemporary necessities in the practical implementation of advanced process control strategies via digital computer-based algorithms. The proposed methodology relies on the derivation of an accurate sampled-data representation of the process, and the subsequent formulation and solution to a nonlinear digital controller synthesis problem. In particular, for the latter two distinct approaches are followed that are both based on the methodological principles of Lyapunov design and rely on a short-horizon model-based prediction and optimization of the rate of“energy dissipation of the system, as it is realized through the time derivative of an appropriately selected Lyapunov function. First, the Lyapunov function is computed by solving the discrete Lyapunov matrix equation. In the second approach however, it is computed by solving a Zubov-like functional equation based on the system\u27s drift vector field. Finally, two examples of a chemical and a biological reactor that both exhibit nonlinear behavior illustrate the main features of the proposed digital controller design method

Empirically modelling the potential effects of changes in temperature and prey availability on the growth of cod larvae in UK shelf seas

It has been hypothesized that changes in zooplankton community structure over the past four decades led to reduced growth and survival of prerecruit Atlantic cod (Gadus morhua) and that this was a key factor underlying poor year classes, contributing to stock collapse, and inhibiting the recovery of stocks around the UK. To evaluate whether observed changes in plankton abundance, species composition and temperature could have led to periods of poorer growth of cod larvae, we explored the effect of prey availability and temperature on early larval growth using an empirical trophodynamic model. Prey availability was parameterized using species abundance data from the Continuous Plankton Recorder. Our model suggests that the observed changes in plankton community structure in the North Sea may have had less impact on cod larval growth, at least for the first 40 days following hatching, than previously suggested. At least in the short term, environmental and prey conditions should be able to sustain growth of cod larvae and environmental changes acting on this early life stage should not limit stock recovery. Crow