Real-Time Control Of Floods Along The Demer River, Belgium, By Means Of MPC In Combination With GA And A Fast Conceptual River Model

Climate model projections show that climate change will further increase the risk of flooding in many regions of the world. There is a need for climate adaptation, but building new infrastructure or additional retention basins has its limits, especially in densely populated areas where open spaces are limited. Another solution is the more efficient use of the existing infrastructure. This research investigates a method for real-time flood control by means of existing gated weirs and retention basins. The method was tested for the specific study area of the Demer basin in Belgium but is generally applicable. Today, retention basins along the Demer River are controlled by means of adjustable gated weirs based on fixed logic rules. However, because of the high complexity of the system, only suboptimal results are achieved by these rules. By making use of precipitation forecasts and combined hydrological-hydraulic river models, the state of the river network can be predicted. To fasten the calculation speed, a conceptual river model was used. The conceptual model was combined with a Model Predictive Control (MPC) algorithm and a Genetic Algorithm (GA). The MPC algorithm predicts the state of the river network depending on the positions of the adjustable weirs in the basin. The GA generates these positions in a semi-random way. Cost functions, based on water levels, were introduced to evaluate the efficiency of each generation, based on flood damage minimization. In the final phase of this research the influence of the most important MPC and GA parameters was investigated by means of a sensitivity study. The results show that the MPC-GA algorithm manages to reduce the total flood volume during the historical event of September 1998 by 46% in comparison with the current regulation. Based on the MPC-GA results, some recommendations could be formulated to improve the logic rules.

Application of multivariable control using artificial neural networks in a debutanizer distillation column

LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

Brain monoaminergic neurons and ventilatory control in vertebrates

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

Neural network based estimation of torque in induction motors for real-time applications

Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this article is to use artificial neural networks for torque estimation with the purpose of best selecting the induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since proposed approach estimates the torque behavior from the transient to the steady state, one of its main contributions is the potential to also be implemented in control schemes for real-time applications. Simulation results are also presented to validate the proposed approach.

Automatic detection of thermal damage in grinding process by artificial neural network

Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

Security constrained optimal active power flow via network model and interior point method

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Optimised placement of control and protective devices in electric distribution systems through reactive tabu search algorithm

Optimised placement of control and protective devices in distribution networks allows for a better operation and improvement of the reliability indices of the system. Control devices (used to reconfigure the feeders) are placed in distribution networks to obtain an optimal operation strategy to facilitate power supply restoration in the case of a contingency. Protective devices (used to isolate faults) are placed in distribution systems to improve the reliability and continuity of the power supply, significantly reducing the impacts that a fault can have in terms of customer outages, and the time needed for fault location and system restoration. This paper presents a novel technique to optimally place both control and protective devices in the same optimisation process on radial distribution feeders. The problem is modelled through mixed integer non-linear programming (MINLP) with real and binary variables. The reactive tabu search algorithm (RTS) is proposed to solve this problem. Results and optimised strategies for placing control and protective devices considering a practical feeder are presented. (c) 2007 Elsevier B.V. All rights reserved.

Evolving Future Internet clean-slate Entity Title Architecture with quality-oriented control-plane extensions

A Internet atual vem sofrendo vários problemas em termos de escalabilidade, desempenho, mobilidade, etc., devido ao vertiginoso incremento no número de usuários e o surgimento de novos serviços com novas demandas, propiciando assim o nascimento da Internet do Futuro. Novas propostas sobre redes orientadas a conteúdo, como a arquitetura Entidade Titulo (ETArch), proveem novos serviços para este tipo de cenários, implementados sobre o paradigma de redes definidas por software. Contudo, o modelo de transporte do ETArch é equivalente ao modelo best-effort da Internet atual, e vem limitando a confiabilidade das suas comunicações. Neste trabalho, ETArch é redesenhado seguindo o paradigma do sobreaprovisionamento de recursos para conseguir uma alocação de recursos avançada integrada com OpenFlow. Como resultado, o framework SMART (Suporte de Sessões Móveis com Alta Demanda de Recursos de Transporte), permite que a rede defina semanticamente os requisitos qualitativos das sessões para assim gerenciar o controle de Qualidade de Serviço visando manter a melhor Qualidade de Experiência possível. A avaliação do planos de dados e de controle teve lugar na plataforma de testes na ilha do projeto OFELIA, mostrando o suporte de aplicações móveis multimídia com alta demanda de recursos de transporte com QoS e QoE garantidos através de um esquema de sinalização restrito em comparação com o ETArch legado

Using network connectance and autonomy analyses to uncover patterns of photosynthetic responses in tropical woody species

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modeling thermal conductivity, specific heat, and density of milk: A neural network approach

The accurate determination of thermophysical properties of milk is very important for design, simulation, optimization, and control of food processing such as evaporation, heat exchanging, spray drying, and so forth. Generally, polynomial methods are used for prediction of these properties based on empirical correlation to experimental data. Artificial neural networks are better Suited for processing noisy and extensive knowledge indexing. This article proposed the application of neural networks for prediction of specific heat, thermal conductivity, and density of milk with temperature ranged from 2.0 to 71.0degreesC, 72.0 to 92.0% of water content (w/w), and 1.350 to 7.822% of fat content (w/w). Artificial neural networks presented a better prediction capability of specific heat, thermal conductivity, and density of milk than polynomial modeling. It showed a reasonable alternative to empirical modeling for thermophysical properties of foods.

Specialised branch-and-bound algorithm for transmission network expansion planning

An algorithm is presented that finds the optimal plan long-term transmission for till cases studied, including relatively large and complex networks. The knowledge of optimal plans is becoming more important in the emerging competitive environment, to which the correct economic signals have to be sent to all participants. The paper presents a new specialised branch-and-bound algorithm for transmission network expansion planning. Optimality is obtained at a cost, however: that is the use of a transportation model for representing the transmission network, in this model only the Kirchhoff current law is taken into account (the second law being relaxed). The expansion problem then becomes an integer linear program (ILP) which is solved by the proposed branch-and-bound method without any further approximations. To control combinatorial explosion the branch- and bound algorithm is specialised using specific knowledge about the problem for both the selection of candidate problems and the selection of the next variable to be used for branching. Special constraints are also used to reduce the gap between the optimal integer solution (ILP program) and the solution obtained by relaxing the integrality constraints (LP program). Tests have been performed with small, medium and large networks available in the literature.

Quality of service control for rt-VBR connections in ATM networks

Nowadays, networks must support applications such as: distance learning, electronic commerce, access to Internet, Intranets and Extranets, voice over IP (Internet Protocol) and many others. These new applications, employing data, voice, and video traffic, require high bandwidth and Quality of Service (QoS). The ATM (Asynchronous Transfer Mode) technology, together with dynamic resource allocation methods, offers network connections that guarantee QoS parameters, such as minimum losses and delays. This paper presents a system that uses Network Management Functions together with dynamic resource allocation for provision of the end-to-end QoS parameters for rt-VBR connections.

Simulation and analysis of a collisionless optical interconnection network

This article describes the simulation and analysis of collisionless optical interconnection network, which the objective is to achieve a high performance level based on a single protocol control. The optical coupler has one shared control channel and N communication channels. Each network node two communication modules one for packet transmission/reception and another for control channel access. We show by simulation that system achieves a high performance and ensures high scalability.

Collagen type VI is a component of the extracellular matrix microfibril network of the prostatic stroma

Stroma-epithelium relationships are of great relevance in prostatic morphogenesis and physiology, However, little knowledge exists about either stromal cells or extracellular matrix composition and arrangement in this system, Ultrastructural analysis revealed the existence of a microfibrillar system which occupies large areas of the rat prostatic stroma, In this work, we have applied immunocytochemistry and an ATP treatment for the ultrastructural identification of collagen type VI microfibrils, aiming at examining its participation in the prostatic microfibrillar network. Immunocytochemistry was also extended to a human case of prostatic nodular hyperplasia, Both methods succeeded in identifying collagen type VI in the rat ventral prostate, Collagen type VI is evenly distributed throughout the stroma but mainly associated with the basal lamina, collagen fibrils, and around the stromal cells, the use of ATP treatment allowed for the discrimination between collagen type VI and elastin-associated microfibrils, and demonstrated that these two classes of microfibrils establish an extended, mixed, and open network. The same aspects of association with the basal lamina, with stromal cells (particularly with smooth muscle cells), and with fibrillar components of the stroma were observed in the human tissue, We suggest that the collagen type VI and elastin-associated microfibril system may be involved in the control of some aspects of cellular behavior and may also play a structural role, maintaining the organ integrity after the deformations occurring under smooth muscle contraction.