Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms in current use. DE operates through similar computational steps as employed by a standard evolutionary algorithm (EA). However, unlike traditional EAs, the DE-variants perturb the current-generation population members with the scaled differences of randomly selected and distinct population members. Therefore, no separate probability distribution has to be used for generating the offspring. Since its inception in 1995, DE has drawn the attention of many researchers all over the world resulting in a lot of variants of the basic algorithm with improved performance. This paper presents a detailed review of the basic concepts of DE and a survey of its major variants, its application to multiobjective, constrained, large scale, and uncertain optimization problems, and the theoretical studies conducted on DE so far. Also, it provides an overview of the significant engineering applications that have benefited from the powerful nature of DE.

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Differential Evolution: A Survey of the State-of-the-Art

There is an increasing demand for dynamic systems to become safer and more reliable This requirement extends beyond the normally accepted safety-critical systems such as nuclear reactors and aircraft, where safety is of paramount importance, to systems such as autonomous vehicles and process control systems where the system availability is vital It is clear that fault diagnosis is becoming an important subject in modern control theory and practice Robust Model-Based Fault Diagnosis for Dynamic Systems presents the subject of model-based fault diagnosis in a unified framework It contains many important topics and methods; however, total coverage and completeness is not the primary concern The book focuses on fundamental issues such as basic definitions, residual generation methods and the importance of robustness in model-based fault diagnosis approaches In this book, fault diagnosis concepts and methods are illustrated by either simple academic examples or practical applications The first two chapters are of tutorial value and provide a starting point for newcomers to this field The rest of the book presents the state of the art in model-based fault diagnosis by discussing many important robust approaches and their applications This will certainly appeal to experts in this field Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research The book is useful for both researchers in academia and professional engineers in industry because both theory and applications are discussed Although this is a research monograph, it will be an important text for postgraduate research students world-wide The largest market, however, will be academics, libraries and practicing engineers and scientists throughout the world

Robust Model-Based Fault Diagnosis for Dynamic Systems

The European Position Paper on Rhinosinusitis and Nasal Polyps 2020 is the update of similar evidence based position papers published in 2005 and 2007 and 2012. The core objective of the EPOS2020 guideline is to provide revised, up-to-date and clear evidence-based recommendations and integrated care pathways in ARS and CRS. EPOS2020 provides an update on the literature published and studies undertaken in the eight years since the EPOS2012 position paper was published and addresses areas not extensively covered in EPOS2012 such as paediatric CRS and sinus surgery. EPOS2020 also involves new stakeholders, including pharmacists and patients, and addresses new target users who have become more involved in the management and treatment of rhinosinusitis since the publication of the last EPOS document, including pharmacists, nurses, specialised care givers and indeed patients themselves, who employ increasing self-management of their condition using over the counter treatments. The document provides suggestions for future research in this area and offers updated guidance for definitions and outcome measurements in research in different settings. EPOS2020 contains chapters on definitions and classification where we have defined a large number of terms and indicated preferred terms. A new classification of CRS into primary and secondary CRS and further division into localized and diffuse disease, based on anatomic distribution is proposed. There are extensive chapters on epidemiology and predisposing factors, inflammatory mechanisms, (differential) diagnosis of facial pain, allergic rhinitis, genetics, cystic fibrosis, aspirin exacerbated respiratory disease, immunodeficiencies, allergic fungal rhinosinusitis and the relationship between upper and lower airways. The chapters on paediatric acute and chronic rhinosinusitis are totally rewritten. All available evidence for the management of acute rhinosinusitis and chronic rhinosinusitis with or without nasal polyps in adults and children is systematically reviewed and integrated care pathways based on the evidence are proposed. Despite considerable increases in the amount of quality publications in recent years, a large number of practical clinical questions remain. It was agreed that the best way to address these was to conduct a Delphi exercise . The results have been integrated into the respective sections. Last but not least, advice for patients and pharmacists and a new list of research needs are included. The full document can be downloaded for free on the website of this journal: http://www.rhinologyjournal.com.

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European Position Paper on Rhinosinusitis and Nasal Polyps 2020

https://users.encs.concordia.ca/~ymzhang/publications/ARC32-2-98Zhang_pp.229-252.pdf

Bibliographical review on reconfigurable fault-tolerant control systems

https://www.ece.lsu.edu/mcu/lawss/add_materials/FaultDetectionPart1.pdf

A Review of Process Fault Detection and Diagnosis Part I : Quantitative Model-Based Methods

Gaseous amines have recently been identified as the key precursors for frequent new particle formation in polluted urban atmospheres. An open question that arises is why amines are abundant in urban areas despite the absence of agricultural emissions. Here, using the Vocus Proton‐Transfer‐Reaction Time‐of‐Flight Mass‐Spectrometry Mobile Laboratory, we present highly time‐resolved and ultrasensitive measurements of amines to elucidate their atmospheric abundance and source distribution over the Yangtze River Delta city cluster. Our results show strong spatiotemporal heterogeneity in atmospheric C2‐ and C3‐amine levels across various landscapes. Unexpectedly, we found that urban areas were ubiquitous hotspots of amines while amine source strength from agricultural areas were rather low. Corroborated by source measurements and source tracers, all of the evidence suggest that nonagricultural emissions are the most important sources responsible for the observed patterns of urban atmospheric amines, implying significant consequences for the global amine emission inventory.

Nonagricultural Emissions Dominate Urban Atmospheric Amines as Revealed by Mobile Measurements

A new scheme to minimise the closed loop randomness for a kind of intelligent welding robot system is presented. It is assumed that the system is subjected from bounded random disturbances. The parameters of controller have been optimised according to a minimum entropy index function by using minimum entropy control method based on an iterative learning frame. As the entropy is the measure of randomness for random variable, the control method advantages to reduce the uncertainty of the closed loop system, which help to obtain a better performance. The iterative learning frame about minimum entropy control has been proposed and is used to optimal the controller parameters. In addition, the convergence of the control algorithm has been analysed. Finally, the effectiveness and feasibility of the proposed control schemes are verified by using an experimental robot.

Minimum entropy control for a class of macro-micro robot based on ILC frame

Presents a direct adaptive neural network control strategy for unknown nonlinear systems which are described by an unknown NARMA model. Taking the neural network as a neuro model of the system, control signals are directly obtained by minimizing either the instant difference or the cummulative differences between a setpoint and the output of the neuro model. An application to a flow rate control system is studied and desired results are obtained.

A direct adaptive neural network control for unknown nonlinear systems

In raw meal calcination process, the target value of decomposition ratio of raw meal (RMDR) is different in easy calcination stage and difficult calcination stage because boundary conditions of raw meal change frequently, where RMDR cannot be guaranteed within its desirable ranges. To solve this problem, an intelligent setting control method is proposed. This method for raw meal calcination process consists of five modules, namely a RMDR target value setting model using subtraction clustering method (SCM) and adaptive-network-based fuzzy inference system containing categorical input (C-ANFIS), a control loop pre-setting model, a feedback compensation model based on fuzzy rules, a feedforward compensation model based on fuzzy rules, and a soft measurement model for RMDR. The proposed method is realized by on-line adjusting the setpoints of control loops with the change of raw meal boundary conditions. This method has been successfully applied to the raw meal calcination process of Jiuganghongda Cement Plant in China and its efficiency has been validated by the practical application results.

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Hong Wang

Papers

Nonagricultural Emissions Dominate Urban Atmospheric Amines as Revealed by Mobile Measurements

Minimum entropy control for a class of macro-micro robot based on ILC frame

A direct adaptive neural network control for unknown nonlinear systems

Intelligent setting control of raw meal calcination proces

Fault detection for a class of nonlinear systems via associative memory neural networks