Parameter estimation algorithms for Hammerstein output error systems using Levenberg–Marquardt optimization method with varying interval measurements

This paper studies the parameter estimation problem of Hammerstein output error autoregressive (OEAR) systems. According to the maximum likelihood principle and the Levenberg-Marquardt optimization method, a maximum likelihood Levenberg-Marquardt recursive (ML-LM-R) algorithm using the varying interval input-output data is proposed. Furthermore, a stochastic gradient algorithm is also derived in order to compare it with the proposed ML-LM-R algorithm. Two numerical examples are provided to verify the effectiveness of the proposed algorithms

Optimisation of a water company’s waste pumping asset base with a focus on energy reduction

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonWater companies use a significant quantity of electricity for the operation of their clean and wastewater assets. Rising energy prices have led to higher energy bills within the water companies, which has increased operating costs. Thus, improvements in demand side energy management are needed to increase efficiency and reduce costs, which forms the premise for this research project. Thames Water Utilities Ltd has identified that improvements in demand side energy management is required and is currently researching various methods to reduce energy consumption. One initiative included the upgrade of a variety of site telemetry assets. By deploying these new telemetry assets, Thames Water Utilities Ltd are more able to liberate the asset data and as such, be able to make informed decisions on how better to control and optimise the target sites, which is where this research project has seen further opportunities. This enhanced telemetry and SCADA infrastructure will enable successful research to further develop an intelligent integrated system that tackles pump scheduling and process control with the emphasis on energy management. The use of modern techniques, such as artificial intelligence, to optimise the network operation is gradually gaining traction. The balance between implementing new technology (with the benefits it may bring) and reluctance to change from the incumbent operating model will always provide challenges in the technology adoption agenda. The main work of this research project included the physical surveying of a wastewater hydraulic catchment, inclusive of all wet well dimensions, lidar overlays, and pump electrical power characteristics. These survey results where then able to be programmed by the research into the company’s' hydraulic model to enable a higher degree of accuracy in the modelling, as well as enabling electrical power as a measurable output. From here, the model was then able to be optimised, focussing on electrical energy as an output variable for reduction. The research concluded that electrical energy consumption over time can be reduced using the aforementioned strategies and as such recommends further work to move from the model environment to physical architecture. It does so with the key message that risk tolerances on water levels must be pre-agreed with hydraulic specialists prior to deployment

Solução com o uso do método dos elementos finitos do problema inverso de danos em placas com perda de material

Tese (Doutorado)—Universidade de Brasília, Programa de Pós-Graduação em Estruturas e Construção Civil, Faculdade de Tecnologia, 2019.As pesquisas em Problemas Inversos têm crescido proporcionando o desenvolvimento tecnológico nas mais diversas áreas da ciência como Medicina, Geofísica, Sensoriamento Remoto, recuperação de imagens, prospecção da crosta terrestre, entre outras. Na Engenharia, importantes trabalhos foram realizados utilizando os Problemas Inversos em aplicações práticas em áreas como Aeronáutica, Engenharia Naval. Na Mecânica os Problemas Inversos são largamente estudados na transferência de calor, assim como também na Engenharia Estrutural. Com elevados níveis de confiabilidade a aplicação às técnicas inversas possibilitam a obtenção de resultados ótimos onde muitas vezes seriam impossíveis de serem obtidos ou, se possível, com custo operacional elevado. A solução do Problema Inverso de identificação de danos em estruturas de placas é abordada nesse trabalho, inicialmente com a apresentação da metodologia da inserção do dano para caracterização do problema e em seguida, por meio da análise estática e dinâmica de modelos numéricos através do Método de Elementos Finitos (MEF) minimiza-se uma função objetivo com a utilização do método dos mínimos quadrados, outros métodos de otimização como Levemberg-Marquardt (LM), Broyden-Fletcher-GoldfarbShanno (BFGS), Davidon-Flecher-Powell (DFP) e o método bio-inspirado de Colônia de Morcegos (CM) que permite avaliar seus dados de resposta em um processo de atualização do modelo de dano, alcançando assim soluções ótimas na localização e quantificação de danos internos em placas. A implementação do processo de análise usando MEF é desenvolvida na linguagem MATLAB® com o auxílio das saídas do software ANSYS® na linguagem APDL. Vários exemplos de localização e quantificação de danos são aplicados com a finalidade de comprovar a sensibilidade e robustez do método proposto.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) e Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).Research in Inverse Problems have grown providing technological development in various areas of science such as medicine, geophysics, remote sensing, image recovery, prospecting the earth's crust, among others. In Engineering, important work was carried out using Inverse Problems in practical applications in areas such as aeronautics, naval engineering. Mechanical In the Inverse Problems are widely studied in heat transfer, and also in structural engineering. With high levels of reliability the application to inverse techniques make it possible to obtain excellent results which often would be impossible to obtain or, if possible, with high operating costs. Solving the Problem plates structures in damage identification Converse is addressed in this work, initially with the presentation of the insertion of the methodology of the damage to characterize the problem and then through static and dynamic analysis of numerical models by Method Finite Element Method (FEM) minimizes up an objective function using the least squares method, that evaluates your response data in a process of updating the damage model, thus achieving optimal solutions in locating and quantifying internal damage on plates. The implementation of the review process using MEF is developed in MATLAB® language with the help of ANSYS® software outs in APDL language. Various examples of the damage location and quantification are applied in order to verify the sensitivity and robustness of the proposed method

Nonlinear Systems

Open Mathematics is a challenging notion for theoretical modeling, technical analysis, and numerical simulation in physics and mathematics, as well as in many other fields, as highly correlated nonlinear phenomena, evolving over a large range of time scales and length scales, control the underlying systems and processes in their spatiotemporal evolution. Indeed, available data, be they physical, biological, or financial, and technologically complex systems and stochastic systems, such as mechanical or electronic devices, can be managed from the same conceptual approach, both analytically and through computer simulation, using effective nonlinear dynamics methods. The aim of this Special Issue is to highlight papers that show the dynamics, control, optimization and applications of nonlinear systems. This has recently become an increasingly popular subject, with impressive growth concerning applications in engineering, economics, biology, and medicine, and can be considered a veritable contribution to the literature. Original papers relating to the objective presented above are especially welcome subjects. Potential topics include, but are not limited to: Stability analysis of discrete and continuous dynamical systems; Nonlinear dynamics in biological complex systems; Stability and stabilization of stochastic systems; Mathematical models in statistics and probability; Synchronization of oscillators and chaotic systems; Optimization methods of complex systems; Reliability modeling and system optimization; Computation and control over networked systems