Controlo tolerante a falhas de um canal de rega

A presente dissertação pretende conceber e implementar um sistema de controlo tolerante a falhas, no canal experimental de rega da Universidade de Évora, utilizando um modelo implementado em MATLAB/SIMULINK®. Como forma de responder a este desafio, analisaram-se várias técnicas de diagnóstico de falhas, tendo-se optado por técnicas baseadas em redes neuronais para o desenvolvimento de um sistema de detecção e isolamento de falhas no canal de rega, sem ter em conta o tipo de sistema de controlo utilizado. As redes neuronais foram, assim, os processadores não lineares utilizados e mais aconselhados em situações onde exista uma abundância de dados do processo, porque aprendem por exemplos e são suportadas por teorias estatísticas e de optimização, focando não somente o processamento de sinais, como também expandindo os horizontes desse processamento. A ênfase dos modelos das redes neuronais está na sua dinâmica, na sua estabilidade e no seu comportamento. Portanto, o trabalho de investigação do qual resultou esta Dissertação teve como principais objectivos o desenvolvimento de modelos de redes neuronais que representassem da melhor forma a dinâmica do canal de rega, de modo a obter um sistema de detecção de falhas que faça uma comparação entre os valores obtidos nos modelos e no processo. Com esta diferença de valores, da qual resultará um resíduo, é possível desenvolver tanto o sistema de detecção como de isolamento de falhas baseados nas redes neuronais, possibilitando assim o desenvolvimento dum sistema de controlo tolerante a falhas, que engloba os módulos de detecção, de isolamento/diagnóstico e de reconfiguração do canal de rega. Em síntese, na Dissertação realizada desenvolveu-se um sistema que permite reconfigurar o processo em caso de ocorrência de falhas, melhorando significativamente o desempenho do canal de rega.

Comportamento dinâmico da rede eléctrica da ilha de São Vicente em Cabo Verde: estabilidade de tensão

Neste trabalho é efectuado, não só o diagnóstico em regime permanente, mas também o estudo, simulação e análise do comportamento dinâmico da rede eléctrica da ilha de São Vicente em Cabo Verde. Os estudos de estabilidade transitória desempenham um importante papel, tanto no planeamento como na operação dos sistemas de potência. Tais estudos são realizados, em grande parte, através de simulação digital no domínio do tempo, utilizando integração numérica para resolver as equações não-lineares que modelam a dinâmica do sistema e dependem da existência de registos reais de perturbação (ex: osciloperturbografia). O objectivo do trabalho será também verificar a aplicabilidade dos requisitos técnicos que as unidades geradoras devem ter, no que concerne ao controlo de tensão, estabelecidos na futura regulamentação europeia desenvolvida pela ENTSO-E (European Network Transmission System Operator for Electricity). De entre os requisitos analisou-se a capacidade das máquinas existentes suportarem cavas de tensão decorrentes de curto-circuitos trifásicos simétricos, Fault Ride Through, no ponto de ligação à rede. Identificaram-se para o efeito os factores que influenciam a estabilidade desta rede, em regime perturbado nomeadamente: (i) duração do defeito, (ii) caracterização da carga, com e sem a presença do sistema de controlo de tensão (AVR) em unidades de geração síncronas. Na ausência de registos reais sobre o comportamento do sistema, conclui-se que este é sensível à elasticidade das cargas em particular do tipo potência constante, existindo risco de perda de estabilidade, neste caso, para defeitos superiores a 5ms sem AVR. A existência de AVR nesta rede afigura-se como indispensável para garantir estabilidade de tensão sendo contudo necessário proceder a uma correcta parametrização.

Nonlinear optimization method for short-term hydro scheduling considering head-dependency

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a new nonlinear optimization method to consider hydroelectric power generation as a function of water discharge and also of the head. Head-dependency is considered on short-term hydro scheduling in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, providing a higher profit at a negligible additional computation time in comparison with a linear optimization method that ignores head-dependency.

Measuring and Controlling the Chaotic Motion of Profits

The study of economic systems has generated deep interest in exploring the complexity of chaotic motions in economy. Due to important developments in nonlinear dynamics, the last two decades have witnessed strong revival of interest in nonlinear endogenous business chaotic models. The inability to predict the behavior of dynamical systems in the presence of chaos suggests the application of chaos control methods, when we are more interested in obtaining regular behavior. In the present article, we study a specific economic model from the literature. More precisely, a system of three ordinary differential equations gather the variables of profits, reinvestments and financial flow of borrowings in the structure of a firm. Firstly, using results of symbolic dynamics, we characterize the topological entropy and the parameter space ordering of kneading sequences, associated with one-dimensional maps that reproduce significant aspects of the model dynamics. The analysis of the variation of this numerical invariant, in some realistic system parameter region, allows us to quantify and to distinguish different chaotic regimes. Finally, we show that complicated behavior arising from the chaotic firm model can be controlled without changing its original properties and the dynamics can be turned into the desired attracting time periodic motion (a stable steady state or into a regular cycle). The orbit stabilization is illustrated by the application of a feedback control technique initially developed by Romeiras et al. [1992]. This work provides another illustration of how our understanding of economic models can be enhanced by the theoretical and numerical investigation of nonlinear dynamical systems modeled by ordinary differential equations.

Dynamical behaviour on the parameter space: new populational growth models proportional to beta densities

We present new populational growth models, generalized logistic models which are proportional to beta densities with shape parameters p and 2, where p > 1, with Malthusian parameter r. The complex dynamical behaviour of these models is investigated in the parameter space (r, p), in terms of topological entropy, using explicit methods, when the Malthusian parameter r increases. This parameter space is split into different regions, according to the chaotic behaviour of the models.

Constructing good deals in discrete time arbitrage-free dynamic pricing models

Recent literature has proved that many classical pricing models (Black and Scholes, Heston, etc.) and risk measures (V aR, CV aR, etc.) may lead to “pathological meaningless situations”, since traders can build sequences of portfolios whose risk leveltends to −infinity and whose expected return tends to +infinity, i.e., (risk = −infinity, return = +infinity). Such a sequence of strategies may be called “good deal”. This paper focuses on the risk measures V aR and CV aR and analyzes this caveat in a discrete time complete pricing model. Under quite general conditions the explicit expression of a good deal is given, and its sensitivity with respect to some possible measurement errors is provided too. We point out that a critical property is the absence of short sales. In such a case we first construct a “shadow riskless asset” (SRA) without short sales and then the good deal is given by borrowing more and more money so as to invest in the SRA. It is also shown that the SRA is interested by itself, even if there are short selling restrictions.

Volatility forecasting with range models: An evaluation of new alternatives to the CARR model

The aim of this paper is to analyze the forecasting ability of the CARR model proposed by Chou (2005) using the S&P 500. We extend the data sample, allowing for the analysis of different stock market circumstances and propose the use of various range estimators in order to analyze their forecasting performance. Our results show that there are two range-based models that outperform the forecasting ability of the GARCH model. The Parkinson model is better for upward trends and volatilities which are higher and lower than the mean while the CARR model is better for downward trends and mean volatilities.

The condensation and ordering of models of empty liquids

We consider a simple model consisting of particles with four bonding sites ("patches"), two of type A and two of type B, on the square lattice, and investigate its global phase behavior by simulations and theory. We set the interaction between B patches to zero and calculate the phase diagram as the ratio between the AB and the AA interactions, epsilon(AB)*, varies. In line with previous work, on three-dimensional off-lattice models, we show that the liquid-vapor phase diagram exhibits a re-entrant or "pinched" shape for the same range of epsilon(AB)*, suggesting that the ratio of the energy scales - and the corresponding empty fluid regime - is independent of the dimensionality of the system and of the lattice structure. In addition, the model exhibits an order-disorder transition that is ferromagnetic in the re-entrant regime. The use of low-dimensional lattice models allows the simulation of sufficiently large systems to establish the nature of the liquid-vapor critical points and to describe the structure of the liquid phase in the empty fluid regime, where the size of the "voids" increases as the temperature decreases. We have found that the liquid-vapor critical point is in the 2D Ising universality class, with a scaling region that decreases rapidly as the temperature decreases. The results of simulations and theoretical analysis suggest that the line of order-disorder transitions intersects the condensation line at a multi-critical point at zero temperature and density, for patchy particle models with a re-entrant, empty fluid, regime. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3657406]

Supporting leadership development by exposure to role models: two case studies

The idiomatic expression “In Rome be a Roman” can be applied to leadership training and development as well. Leaders who can act as role models inspire other future leaders in their behaviour, attitudes and ways of thinking. Based on two examples of current leaders in the fields of Politics and Public Administration, I support the idea that exposure to role models during their training was decisive for their career paths and current activities as prominent characters in their profession. Issues such as how students should be prepared for community or national leadership as well as cross-cultural engagement are raised here. The hypothesis of transculturalism and cross-cultural commitment as a factor of leadership is presented. Based on current literature on Leadership as well as the presented case studies, I expect to raise a debate focusing on strategies for improving leaders’ training in their cross-cultural awareness.

Long-term price range forecast applied to risk management using regression models

Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.

Dynamical analysis in growth models: Blumberg’s equation

We present a new dynamical approach to the Blumberg's equation, a family of unimodal maps. These maps are proportional to Beta(p, q) probability densities functions. Using the symmetry of the Beta(p, q) distribution and symbolic dynamics techniques, a new concept of mirror symmetry is defined for this family of maps. The kneading theory is used to analyze the effect of such symmetry in the presented models. The main result proves that two mirror symmetric unimodal maps have the same topological entropy. Different population dynamics regimes are identified, when the intrinsic growth rate is modified: extinctions, stabilities, bifurcations, chaos and Allee effect. To illustrate our results, we present a numerical analysis, where are demonstrated: monotonicity of the topological entropy with the variation of the intrinsic growth rate, existence of isentropic sets in the parameters space and mirror symmetry.

Derivative-free optimization and filter methods to solve nonlinear constrained problems

In real optimization problems, usually the analytical expression of the objective function is not known, nor its derivatives, or they are complex. In these cases it becomes essential to use optimization methods where the calculation of the derivatives, or the verification of their existence, is not necessary: the Direct Search Methods or Derivative-free Methods are one solution. When the problem has constraints, penalty functions are often used. Unfortunately the choice of the penalty parameters is, frequently, very difficult, because most strategies for choosing it are heuristics strategies. As an alternative to penalty function appeared the filter methods. A filter algorithm introduces a function that aggregates the constrained violations and constructs a biobjective problem. In this problem the step is accepted if it either reduces the objective function or the constrained violation. This implies that the filter methods are less parameter dependent than a penalty function. In this work, we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of the simplex method and filter methods. This method does not compute or approximate any derivatives, penalty constants or Lagrange multipliers. The basic idea of simplex filter algorithm is to construct an initial simplex and use the simplex to drive the search. We illustrate the behavior of our algorithm through some examples. The proposed methods were implemented in Java.

Derivative-free nonlinear optimization filter simplex

The filter method is a technique for solving nonlinear programming problems. The filter algorithm has two phases in each iteration. The first one reduces a measure of infeasibility, while in the second the objective function value is reduced. In real optimization problems, usually the objective function is not differentiable or its derivatives are unknown. In these cases it becomes essential to use optimization methods where the calculation of the derivatives or the verification of their existence is not necessary: direct search methods or derivative-free methods are examples of such techniques. In this work we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of simplex and filter methods. This method neither computes nor approximates derivatives, penalty constants or Lagrange multipliers.

An Extension of Gompertzian Growth Dynamics Weibull and Frechet Models

In this work a new probabilistic and dynamical approach to an extension of the Gompertz law is proposed. A generalized family of probability density functions, designated by Beta* (p, q), which is proportional to the right hand side of the Tsoularis-Wallace model, is studied. In particular, for p = 2, the investigation is extended to the extreme value models of Weibull and Frechet type. These models, described by differential equations, are proportional to the hyper-Gompertz growth model. It is proved that the Beta* (2, q) densities are a power of betas mixture, and that its dynamics are determined by a non-linear coupling of probabilities. The dynamical analysis is performed using techniques of symbolic dynamics and the system complexity is measured using topological entropy. Generally, the natural history of a malignant tumour is reflected through bifurcation diagrams, in which are identified regions of regression, stability, bifurcation, chaos and terminus.

Mass-degenerate Higgs bosons at 125 GeV in the two-Higgs-doublet model

The analysis of the Higgs boson data by the ATLAS and CMS Collaborations appears to exhibit an excess of h -> gamma gamma events above the Standard Model (SM) expectations, whereas no significant excess is observed in h -> ZZ* -> four lepton events, albeit with large statistical uncertainty due to the small data sample. These results (assuming they persist with further data) could be explained by a pair of nearly mass-degenerate scalars, one of which is an SM-like Higgs boson and the other is a scalar with suppressed couplings to W+W- and ZZ. In the two-Higgs-doublet model, the observed gamma gamma and ZZ* -> four lepton data can be reproduced by an approximately degenerate CP-even (h) and CP-odd (A) Higgs boson for values of sin (beta - alpha) near unity and 0: 70 less than or similar to tan beta less than or similar to 1. An enhanced gamma gamma signal can also arise in cases where m(h) similar or equal to m(H), m(H) similar or equal to m(A), or m(h) similar or equal to m(H) similar or equal to m(A). Since the ZZ* -> 4 leptons signal derives primarily from an SM-like Higgs boson whereas the gamma gamma signal receives contributions from two (or more) nearly mass-degenerate states, one would expect a slightly different invariant mass peak in the ZZ* -> four lepton and gamma gamma channels. The phenomenological consequences of such models can be tested with additional Higgs data that will be collected at the LHC in the near future. DOI: 10.1103/PhysRevD.87.055009.