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

An observer for nonlinear systems is constructed under rather general technical assumptions (the fact that some functions are globally Lipschitz). This observer works either for autonomous systems or for nonlinear systems that are observable for any input. A tentative application to biological systems is described. >

A simple observer for nonlinear systems applications to bioreactors

Thermophysical Properties Research Literature Retrieval Guide Edited by Y. S. Touloukian, J. K. Gerritsen and N. Y. Moore Second edition, revised and expanded. Book 1: Pp. xxi + 819. Book 2: Pp.621. Book 3: Pp. ix + 1315. (New York: Plenum Press, 1967.) n.p.

/pdf/heat-and-mass-transfer-1yaijfx8vp.pdf

Heat and Mass Transfer

This paper provides a survey of modern nonlinear filtering methods for attitude estimation. Early applications relied mostly on the extended Kalman filter for attitude estimation. Since these applications, several new approaches have been developed that have proven to be superior to the extended Kalman filter. Several of these approaches maintain the basic structure of the extended Kalman filter, but employ various modifications in order to provide better convergence or improve other performance characteristics. Examples of such approaches include: filter QUEST, extended QUEST and the backwards-smoothing extended Kalman filter. Filters that propagate and update a discrete set of sigma points rather than using linearized equations for the mean and covariance are also reviewed. A twostep approach is discussed with a first-step state that linearizes the measurement model and an iterative second step to recover the desired attitude states. These approaches are all based on the Gaussian assumption that the probability density function is adequately specified by its mean and covariance. Other approaches that do not require this assumption are reviewed, Associate Professor, Department of Mechanical & Aerospace Engineering. Email: johnc@eng.buffalo.edu. Associate Fellow AIAA. Aerospace Engineer, Guidance, Navigation and Control Systems Engineering Branch. Email: Landis.Markley@nasa.gov. Fellow AIAA. Postdoctoral Research Fellow, Department of Mechanical & Aerospace Engineering. Email: cheng3@eng.buffalo.edu. Member AIAA.

/pdf/survey-of-nonlinear-attitude-estimation-methods-4tcu9nk5p8.pdf

Survey of nonlinear attitude estimation methods

We present a differential geometric approach to the problem of fault detection and isolation for nonlinear systems. A necessary condition for the problem to be solvable is derived in terms of an unobservability distribution, which is computable by means of suitable algorithms. The existence and regularity of such a distribution implies the existence of changes of coordinates in the state and in the output space which induce an "observable" quotient subsystem unaffected by all fault signals but one. For this subsystem, a fault detection filter is designed.

A geometric approach to nonlinear fault detection and isolation

Nonlinear estimation strategies for parameter estimation in chemical reactors

Since 1998 [3], the yearly mean publication rate of papers using a first principle model for control has been multiplied by 11! This increase is quiet similar to the increase of the control papers in drying based on optimal control strategies, like MPC. With 60 000 products dried and 100 dryer types used worldwide [1], a real potential exists. With control tools like MPC, it is expected that the industrial drying operation will continue to improve its energy efficiency while enhancing product quality and reducing the negative environmental impact of dryers.

https://hal.archives-ouvertes.fr/hal-00388216/document

Benefits in using model based predictive control during drying and lyophilisation

In this paper, a nonlinear high gain observer is developed to reconstruct the full state of an olive oil waste esterification process This operation is taking place in a semi-continuous stirred tank reactor The plant model, as most of the chemical processes, presents a high level of non linearities and interconnections between states Most of the works developed around such model are based on a canonical form of the model or in single input single output structure We show, in this work, that it is possible to synthesis a high gain based full observer for a multi input multi output system and to ensure good applicability of a such observer The results are validated on real measurements of the plant The second part is devoted to performances' comparison between our observer and the well used observer for such nonlinear systems, the Extended Kalman Filter The comparison shows that the high gain observer presents better results in precision and application limitations

A nonlinear high gain observer for an olive oil waste esterification in a continuous stirred tank reactor

In most of the literature, the design of a high gain observer is based on normal forms. In the case where a nonlinear system, which is characterized by a normal form, is observable independently on the input, it is shown here that the gain of this observer does not require any differential equation. In this paper, we also investigate the problem of the high gain observer of a class of nonlinear systems which are not observable independently on the input. It is shown that if the input satisfies some observability condition, then an exponential observer, whose gain derived from a Lyapunov differential equation, can be designed.

https://hal.archives-ouvertes.fr/hal-00469595/document

Nonlinear observers synthesis based on strongly persistent inputs

In this paper, the error observer linearization is extended to a class of observable cascade systems which contains state affine systems up to output injection. First, we give a theoretical result which states necessary and sufficient conditions. Next, we give an algorithm permitting to calculate a system of coordinates in which a nonlinear system takes the desired cascade observable form.

/pdf/nonlinear-observer-based-on-observable-cascade-form-56it2fnatq.pdf

Hassan Hammouri

Papers

Nonlinear estimation strategies for parameter estimation in chemical reactors

Benefits in using model based predictive control during drying and lyophilisation

A nonlinear high gain observer for an olive oil waste esterification in a continuous stirred tank reactor

Nonlinear observers synthesis based on strongly persistent inputs

Nonlinear observer based on observable cascade form