Complex order control for improved loop-shaping in precision positioning

This paper presents a complex order filter developed and subsequently integrated into a PID-based controller design. The nonlinear filter is designed with reset elements to have describing function based frequency response similar to that of a linear (practically non-implementable) complex order filter. This allows for a design which has a negative gain slope and a corresponding positive phase slope as desired from a loop-shaping controller-design perspective. This approach enables improvement in precision tracking without compromising the bandwidth or stability requirements. The proposed designs are tested on a planar precision positioning stage and performance compared with PID and other state-of-the-art reset based controllers to showcase the advantages of this filter

Fractional control of an offshore wind system

This paper presents a simulation on a way to improve the ability of an offshore wind system to recover from a fault in the rectifier converter. The system comprises a semi-submersible platform, a variable speed wind turbine, a synchronous generator with permanent magnets (PMSG), and a five-level multiple point diode clamped converter. The recovery is improved by shielding the DC link of the converter during the fault using as further equipment a redox vanadium flow battery. A fractional PI controller is used for the PMSG and the converter

Fractional Order Processing of Satellite Images

Nowadays, satellite images are used in many applications, and their automatic processing is vital. Conventional integer grey-scale edge detection algorithms are often used for this. This study shows that the use of color-based, fractional order edge detection may enhance the results obtained using conventional techniques in satellite images. It also shows that it is possible to find a fixed set of parameters, allowing automatic detection while maintaining high performance

Discrete lot sizing and scheduling on parallel machines: description of a column generation approach

In this work, we study the discrete lot sizing and scheduling problem (DSLP) in identical parallel resources with (sequence-independent) setup costs and inventory holding costs. We propose a Dantzig-Wolfe decomposition of a known formulation and describe a branch-and-price and column generation procedure to solve the problem to optimality. Preliminary results show that the lower bounds provided by the reformulated model are stronger than the lower bounds provided by the linear programming relaxation of the original model

A column generation approach to the discrete lot sizing and scheduling problem on parallel machines

In this work, we study the discrete lot sizing and scheduling problem (DSLP) in identical parallel resources with (sequence-independent) setup costs and inventory holding costs. We propose a Dantzig-Wolfe decomposition of a known formulation and describe a branch-and-price and column generation procedure to solve the problem to optimality. The results show that the lower bounds provided by the reformulated model are stronger than the lower bounds provided by the linear programming (LP) relaxation of the original model.info:eu-repo/semantics/publishedVersio

Parallel machine scheduling using free software: an application

We will show how to implement large scale optimization by only using freely available software tools. We solve exactly a parallel machine scheduling problem with identical parallel machines and malleable tasks, subject to arbitrary release dates and due dates. The objective is to minimize a function of late work and setup costs. We use the COIN-OR BCP framework to implement column generation to solve a model that results from a Dantzig-Wolfe decomposition, and also CRIFOR MCFZIB to solve an equivalent network flow model. Computational results are presented

Solving a multiprocessor problem by column generation and branch-and-price

This work presents an algorithm for solving exactly a scheduling problem with identical parallel machines and malleable tasks, subject to arbitrary release dates and due dates. The objective is to minimize a function of late work and setup costs. A task is malleable if we can freely change the set of machines assigned to its processing over the time horizon. We present an integer programming model, a Dantzig-Wolfe decomposition reformulation and its solution by column generation. We also developed an equivalent network flow model, used for the branching phase. Finally, we carried out extensive computational tests to verify the algorithm’s efficiency and to determine the model’s sensitivity to instance size parameters: the number of machines, the number of tasks and the size of the planning horizon

How Many Fractional Derivatives Are There?

Funding: This work was partially funded by National Funds through the FCT-Foundation for Science and Technology within the scope of the CTS Research Unit—Center of Technology and Systems/UNINOVA/FC /NOVA, under the reference UIDB/00066/2020, and also by FCT through IDMEC, under LAETA, project UID/EMS/50022/2020. Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.In this paper, we introduce a unified fractional derivative, defined by two parameters (order and asymmetry). From this, all the interesting derivatives can be obtained. We study the one-sided derivatives and show that most known derivatives are particular cases. We consider also some myths of Fractional Calculus and false fractional derivatives. The results are expected to contribute to limit the appearance of derivatives that differ from existing ones just because they are defined on distinct domains, and to prevent the ambiguous use of the concept of fractional derivative.publishersversionpublishe

Machine learning and natural language processing for prediction of human factors in aviation incident reports

In the aviation sector, human factors are the primary cause of safety incidents. Intelligent prediction systems, which are capable of evaluating human state and managing risk, have been developed over the years to identify and prevent human factors. However, the lack of large useful labelled data has often been a drawback to the development of these systems. This study presents a methodology to identify and classify human factor categories from aviation incident reports. For feature extraction, a text pre-processing and Natural Language Processing (NLP) pipeline is developed. For data modelling, semi-supervised Label Spreading (LS) and supervised Support Vector Machine (SVM) techniques are considered. Random search and Bayesian optimization methods are applied for hyper-parameter analysis and the improvement of model performance, as measured by the Micro F1 score. The best predictive models achieved a Micro F1 score of 0.900, 0.779, and 0.875, for each level of the taxonomic framework, respectively. The results of the proposed method indicate that favourable predicting performances can be achieved for the classification of human factors based on text data. Notwithstanding, a larger data set would be recommended in future research

Fractional Calculus as Modelling Tool

Cancer is a complex disease, responsible for a significant portion of global deaths. The increasing prioritisation of know-why over know-how approaches in biological research has favoured the rising use of both white- and black-box mathematical techniques for cancer modelling, seeking to better grasp the multi-scale mechanistic workings of its complex phenomena (such as tumour-immune interactions, drug resistance, tumour growth and diffusion, etc.). In light of this wide-ranging use of mathematics in cancer modelling, the unique memory and non-local properties of Fractional Calculus (FC) have been sought after in the last decade to replace ordinary differentiation in the hypothesising of FC’s superior modelling of complex oncological phenomena, which has been shown to possess an accumulated knowledge of its past states. As such, this review aims to present a thorough and structured survey about the main guiding trends and modelling categories in cancer research, emphasising in the field of oncology FC’s increasing employment in mathematical modelling as a whole. The most pivotal research questions, challenges and future perspectives are also outlined.publishersversionpublishe