Predictive feedback control using a multiple model approach

A new method of designing predictive controllers for SISO systems is presented. The controller selects the model used in the design of the control law from a given set of models according to a switching rule based on output prediction errors. The goal is to design, at each sample instant, a feedback control law that ensures robust stability of the closed–loop system and gives better performance for the current operating point. The overall multiple model predictive control scheme quickly identifies the closest linear model to the dynamics of the current operating point, and carries out an automatic reconfiguration of the control system to achieve a better performance. The results are illustrated with simulations of a continuous stirred tank reactor

Adaptive Robust Control of Biomass Fuel Co-Combustion Process

The share of biomass in energy production is constantly growing. This is caused by environmental and industry standards and EU guidelines. Biomass is used in the process of co-firing in large power plants and industrial installations. In the existing power stations, biomass is milled and burned simultaneously with coal. However, low-emission combustion techniques, including biomass co-combustion, have some negative side effects that can be split into two categories. The direct effects influence the process control stability, whereas the indirect ones on combustion installations via increased corrosion or boiler slagging. The effects can be minimised using additional information about the process. The proper combustion diagnosis as well as an appropriate, robust control system ought to be applied. The chapter is devoted to the analysis of modern, robust control techniques for complex power engineering applications

Beyond rational expectations: the effects of heuristic switching in an overlapping generations model

We explore the transitional dynamics in an Overlapping Generations framework with and without heuristic switching. Agents use simple heuristics to forecast the interest rate and the real wage. The fraction of agents using a specific heuristic depends on its relative forecasting performance. In the absence of heuristic switching, the results indicate that there is a lot of variation in the transitional dynamics over different parameter values and heuristics. They might even oscillate or diverge. Including heuristic switching has two advantages. First, it decreases the variation in the transitional dynamics significantly. Second, it has a stabilising effect on oscillating or diverging transitional dynamics

The Dollar Exchange Rate, Adjustment to the Purchasing Power Parity, and the Interest Rate Differential

This study applies a Markov switching error correction model to describe the single most important real exchange rate (Deutsche mark versus US dollar) over the flexible exchange rates period from 1973 to 2004. We show an alternative way of modelling non-linear adjustment to the purchasing power parity (PPP) besides standard threshold models. The model merges the two possible sources of non-linearity by additionally allowing the probability of a mean-reverting regime to increase with the distance from PPP. The interest rate differential as an additional determinant of real exchange rate behaviour in a Markov switching framework is introduced in the model. The study finds that the real dollar exchange rate during the post-Bretton Woods era is well described by a Markov switching error correction model with (PPP) as long-run equilibrium. There is one mean reversion regime where PPP and the interest parity condition are valid. Contrary, the second regime is characterised by persistent mean aversion, where a regime switch does not become more likely with increasing distance from PPP. The unconditional half-life of shocks is about 1.5 years

Global stabilisation of continuous bioreactors: tools for analysis and design of feeding laws

[EN] This work revisits the dynamic behaviour of stirred continuous reactors in which a single bioreaction with unknown kinetics occurs. Conditions on the feeding strategy to avoid washing out the biomass and falling in batch operation are obtained. These conditions derive in a closed positively invariant region including the desired operating point. It is stated that no closed orbits may exist in this region and, furthermore, that no fixed point exists but on one of its borders. Therefore, global stability is achieved by finding a feeding law that fulfils the aforementioned invariant conditions and gives a single equilibrium for a first-order dynamics. These results are useful to determine the stability properties of different control laws and, more importantly, to design new ones. The main advantages of the proposed approach are its simplicity and that, differing from previous results, input saturation does not affect stability results. The potentiality of the developed tools is illustrated by means of classical and novel feeding laws. (C) 2017 Elsevier Ltd. All rights reserved.Financed by I216-2016 (UNLP), PICT2014-2394 (ANPCyT) and PIP112-2015-01-00837 (CONICET), Argentina; and by DPI2014-55276-C5-1-R MINECO/AEI/FEDER, UE. The material in this paper was not presented at any conference.De Battista, H.; Jamilis, M.; Garelli, F.; Picó, J. (2018). Global stabilisation of continuous bioreactors: tools for analysis and design of feeding laws. Automatica. 89:340-348. https://doi.org/10.1016/j.automatica.2017.12.041S3403488

Complex systems in financial economics: Applications to interbank and stock markets

Complex systems are characterised by strong interaction at the micro level that can induce large changes at the macro level. This thesis applies the theory of complex systems to the interbank market (Part I) and the stock market (Part II). Evidence found in data from the Netherlands and the US makes clear in what sense these markets are complex systems. The observed phenomena are explained by modelling the adaptive behaviour of financial agents, for example how they form their trading relationships or how they choose investment strategies. The applications help to understand the mechanisms behind the emergence of the financial-economic crisis in 2007 and 2008, and relate to the debate on policy measures aiming to prevent a future crisis of this kind

Diffusion maps embedding and transition matrix analysis of the large-scale flow structure in turbulent Rayleigh--B\'enard convection

By utilizing diffusion maps embedding and transition matrix analysis we investigate sparse temperature measurement time-series data from Rayleigh--B\'enard convection experiments in a cylindrical container of aspect ratio $\Gamma=D/L=0.5$ between its diameter ($D$) and height ($L$). We consider the two cases of a cylinder at rest and rotating around its cylinder axis. We find that the relative amplitude of the large-scale circulation (LSC) and its orientation inside the container at different points in time are associated to prominent geometric features in the embedding space spanned by the two dominant diffusion-maps eigenvectors. From this two-dimensional embedding we can measure azimuthal drift and diffusion rates, as well as coherence times of the LSC. In addition, we can distinguish from the data clearly the single roll state (SRS), when a single roll extends through the whole cell, from the double roll state (DRS), when two counter-rotating rolls are on top of each other. Based on this embedding we also build a transition matrix (a discrete transfer operator), whose eigenvectors and eigenvalues reveal typical time scales for the stability of the SRS and DRS as well as for the azimuthal drift velocity of the flow structures inside the cylinder. Thus, the combination of nonlinear dimension reduction and dynamical systems tools enables to gain insight into turbulent flows without relying on model assumptions