Antonio A. Alonso

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The dynamic optimization (open loop optimal control) of non-linear bioprocesses is considered in this contribution. These processes can be described by sets of non-linear differential and algebraic equations (DAEs), usually subject to constraints in the state and control variables. A review of the available solution techniques for this class of problems is(More)
Mathematical models provide abstract representations of the information gained from experimental observations on the structure and function of a particular biological system. Conferring a predictive character on a given mathematical formulation often relies on determining a number of non-measurable parameters that largely condition the model's response.(More)
In this letter we show that closed reversible chemical reaction networks with independent elementary reactions admit a global pseudoHamiltonian structure which is at least locally dissipative around any equilibrium point. The structure matrix of the Hamiltonian description reflects the graph topology of the reaction network and it is a smooth function of(More)
SUMMARY Model based optimization can be successfully used to improve the design and operation of bioreactors. In this contribution, we present a review of this area, especially focusing on the dynamic optimization of fed-batch bioreactors, a class of problems which has attracted (and continues to receive) huge attention. Both classical and more novel(More)
In this paper we explore connections between the underlying physics of dissipative systems and nonlinear robust control. In particular, we concentrate on the problem of stabilizing stationary solutions of nonlinear dissipative systems with states distributed in space. Dissipative systems are equipped with an entropy function which we employ to relate(More)
In this contribution, computer-aided optimization is presented as the ultimate tool to improve food processing. The state of the art is reviewed, especially focusing in recent developments using modern optimization techniques. Their potential for industrial applications is also discussed in the light of several important examples. Finally, future trends and(More)
The inference of biological networks from high-throughput data has received huge attention during the last decade and can be considered an important problem class in systems biology. However, it has been recognized that reliable network inference remains an unsolved problem. Most authors have identified lack of data and deficiencies in the inference(More)