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

The finite-time tracking control for reusable launch vehicle with unmatched disturbance is investigated. An adaptive-multivariable-disturbance-compensation scheme is proposed to provide the estimation for external disturbances where the bounds of the perturbations are not known. Based on the estimation, a continuous multivariable homogeneity second order sliding mode controller is designed to ensure that the attitude tracking is achieved in finite time. A proof of the finite-time convergence of the closed-loop system under the integrated controller and disturbance observer is derived using the Lyapunov technique. The features of the proposed control scheme are that it does not require any information on the bounds of the disturbance and its gradient except for their existence. At the same time, the finite-time convergence, nominal performance recovery, and chattering alleviation are guaranteed. Finally, some simulation tests are provided to demonstrate the effectiveness of the proposed control scheme.

Finite-Time Reentry Attitude Control Based on Adaptive Multivariable Disturbance Compensation

Design of new fault diagnosis and fault tolerant control scheme for non-Gaussian singular stochastic distribution systems

Differential Evolution (DE) has gathered a reputation for being a powerful yet simple global optimiser with continually outperforming many of the already existing stochastic and direct search global optimisation techniques. It is however well established that DE is particularly sensitive to its control parameters, most notably the mutation weighting factor F. This sensitivity is further studied here and a simple randomised self-adaptive scheme is proposed for the DE mutation weighting factor F. The performance of this algorithm is studied with the use of several benchmark problems and applied to a difficult control systems design case study.

A simple self-adaptive Differential Evolution algorithm with application on the ALSTOM gasifier

For dynamic systems with actuator faults, sensor faults, input disturbances, and measurement noises, a novel high-gain estimation technique is presented in this paper to estimate system states, actuator faults, and sensor faults simultaneously. The key idea is to represent faults as auxiliary system states so that a descriptor system representation can be formulated. By using the estimated state and fault signals, a fault-tolerant controller design approach is developed, where the closed-loop dynamic system can still be guaranteed to operate normally when actuator and sensor faults occur. It has been shown that in the proposed design framework, the actuator fault, sensor fault, input disturbance, and measurement noise can appear simultaneously and can be allowed to be in different bounded forms. Finally, the proposed algorithm is applied to the simulation study of a three-shaft gas turbine system and desired results have been obtained.

High-Gain Estimator and Fault-Tolerant Design With Application to a Gas Turbine Dynamic System

For systems with both state and input time delays, a novel state and sensor fault observer is proposed in this paper to estimate system states and sensor faults simultaneously. In this design, a descriptor system approach and a linear matrix inequality technique are adopted, where the considered sensor fault may be in any form, even unbounded. Unbounded sensor faults will make the system fail unavoidably; it is indispensable to derive a reliable control scheme against sensor failures. Using the estimated state and sensor fault, a reliable observer-based controller is proposed, which makes the system work well no matter whether sensor faults occur or not. The present approaches are next extended to the case for systems with multiple time delays. Finally, a simulation example of the network of three cascaded reactors is used to illustrate the design procedure and demonstrate the efficiency of the present techniques.

Hong Wang

Papers

Finite-Time Reentry Attitude Control Based on Adaptive Multivariable Disturbance Compensation

Design of new fault diagnosis and fault tolerant control scheme for non-Gaussian singular stochastic distribution systems

A simple self-adaptive Differential Evolution algorithm with application on the ALSTOM gasifier

High-Gain Estimator and Fault-Tolerant Design With Application to a Gas Turbine Dynamic System

Reliable Observer-Based Control Against Sensor Failures for Systems With Time Delays in Both State and Input