https://www2.econ.iastate.edu/tesfatsi/DeepLearningInNeuralNetworksOverview.JSchmidhuber2015.pdf

Deep learning in neural networks

A review on machinery diagnostics and prognostics implementing condition-based maintenance

This book is downloadable from http://www.irisa.fr/sisthem/kniga/. Many monitoring problems can be stated as the problem of detecting a change in the parameters of a static or dynamic stochastic system. The main goal of this book is to describe a unified framework for the design and the performance analysis of the algorithms for solving these change detection problems. Also the book contains the key mathematical background necessary for this purpose. Finally links with the analytical redundancy approach to fault detection in linear systems are established. We call abrupt change any change in the parameters of the system that occurs either instantaneously or at least very fast with respect to the sampling period of the measurements. Abrupt changes by no means refer to changes with large magnitude; on the contrary, in most applications the main problem is to detect small changes. Moreover, in some applications, the early warning of small - and not necessarily fast - changes is of crucial interest in order to avoid the economic or even catastrophic consequences that can result from an accumulation of such small changes. For example, small faults arising in the sensors of a navigation system can result, through the underlying integration, in serious errors in the estimated position of the plane. Another example is the early warning of small deviations from the normal operating conditions of an industrial process. The early detection of slight changes in the state of the process allows to plan in a more adequate manner the periods during which the process should be inspected and possibly repaired, and thus to reduce the exploitation costs.

Detection of abrupt changes: theory and application

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

Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results

This paper looks at the application of Variable Structure Control (VSC) theory to the problem of lateral control of a Machan aircraft. A full state switching VSC system is developed and is shown to produce dynamic responses in roll and yaw which are functions of pitch and roll angle. A reduced state switching VSC system is subsequently defined to produce a more invariant performance.

Reduced order variable structure control of the lateral motion of an aircraft

A time-domain LPV H_/H∞ fault detection filter

The number and severity of earthquakes has led to a growing interest in control systems capable of improving the safety and integrity of buildings and other structures that are subject to violent vibration control on each building floor is considered as a local control problem within the hierarchical two-level structure. The distributed control system, based on receding horizon control, gives rise to a “plug and play” structure. If individual controller subsystems fail the global can be maintained. An example of a building structure excited by standard seismic data with semi-active hydraulic floor actuators is described. Results demonstrate the fault tolerance of the plug and play distributed system as the coordinator compensates for actuator malfunctions. The distributed system performance is compared with a single level H-∞ controller as a robust system benchmark.

Ron J. Patton

Papers

Reduced order variable structure control of the lateral motion of an aircraft

A time-domain LPV H_/H∞ fault detection filter

Fault tolerant plug and play vibration control in building structures

Robust Fault Estimation and Performance Evaluation based upon the ADDSAFE Benchmark Model

Non-linear Viscous and Friction Effects on a Heaving Point Absorber Dynamics and Latching Control Performance