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

A new method is presented for the design of simply structured multivariable controllers that can explicitly meet mixed sensitivity robust performance and robust stability criteria. Currently, most established robust controller design methods are synthesis-based and produce controllers that are often of much higher order than the plant. Based on the technique of diagonal dominance, this method proposes a novel means of directly 'designing' a robust controller, which among others, has the benefit that its order can be determined by the designer. By using elementary algebra, it is shown that the Gershgorin disks of a matrix may also be used to bind its singular values in addition to the eigenvalues. This fact is then exploited to create simple envelopes that bind the singular values of the sensitivity and complementary sensitivity functions, which are subsequently used in the design of the diagonal dominance-based controller such that the mixed criteria on the loop transfer function sensitivities may be met. As with other mixed sensitivity design techniques, this method does not guarantee that a controller is feasible for any set of arbitrary specifications. The method is applied to design a mixed-sensitivity controller for a mathematical model of the Rolls-Royce gas-turbine engine.

Design of simply structured robust controllers

This paper presents a solution for the design of a time-varying and parametric output feedback controller for known general non-linear dynamic systems subjected to linear output structure. The controller consists of two parts: an adaptive observer and a time-varying controller. Under a certain assumption on the non-linear dynamics of the system, a stable and non-linear adaptive observer can be firstly built. This observer can then be logically combined with any pre-specified smooth non-linear controller that uses the estimated state feedback with a tuning parameter. A combined parameter dependent Lyapunov function is constructed and used to formulate an effective tuning rule for the time-varying parameters involved in both the observer and the controller. With this selection of the tuning rule, it has been shown that the closed loop system is stable and the output can be controlled to converge to zero. An example is included to illustrate the use of the proposed methods and encouraging results have been obtained.

A generalised time-varying output feedback controller for non-linear systems

Based on the recently developed rule based identification algorithm of Wang and Jones (1991), this paper presents a new algorithm for controller tuning in unit feedback control systems. In the paper, the rule based identification algorithm is used directly to identify the model between the reference step input and the integral of the tracking error. Two stages of tuning are proposed. In the first stage, the correct structure of the controller is chosen by monitoring the integral of the tracking error. This enables the realisation of perfect steady-state tracking. In the second stage, the estimated model is used to tune the controller gains in order to provide an improved dynamic performance for the closed-loop response. The results of applying the algorithm to the stimulation of a real process are given.

Controller tuning via rule based identification

Almost all multivariable design techniques impose a fixed structure on the final controller. This may be centralised or (block) decentralised, but it is typically the case that the structure is either not adequate or excessive. This work concerns an alternative design method whereby the controller structure is not fixed, but instead is also a design objective. Based on this a generic cost function is determined where both the structure of the controller and the performance of the resulting closed loop system appear as minimisation terms. It has been shown that there exists an optimal weighting such that the optimisation of the weighted sum of these two terms will always result in a unique reduced structure controller. The methodology is then successfully applied to the model of a gas-turbine.

Hong Wang

Papers

Design of simply structured robust controllers

A generalised time-varying output feedback controller for non-linear systems

Controller tuning via rule based identification

Controller structure selection using the reduced structure control methodology

Minimum entropy control using B-spline square root models