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 describes the development and testing of the implementation of a linear parameter varying (LPV) fault tolerant control (FTC) approach to hydraulic pitch actuation for an off-shore wind turbine (OWT) system with independent pitch actuators. The study involves two separate actuator fault scenarios. In the first scenario the pitch actuator position sensor signal is considered to be stuck at a fixed value. In this case, a fault hiding approach is used to compensate for this fault in the control system, as a form of sensor FTC scheme with fault estimation. The second fault scenario is caused either by a drop in pressure in the hydraulic supply system or the high air content in the oil. In this case, the fault-free pitch actuator systems are both utilized to synchronize all three pitch systems in order to prevent further damage caused by unbalanced structural loads.

Active FTC for hydraulic pitch system for an off-shore wind turbine

A robust actuator multiplicative fault estimation approach is designed by combining the unknown input-decoupling principle and H∞ optimization. The fault is constructed as an augmented system state and estimated by the proposed observer. In this observer, the unknown input-decoupling principle is used to decouple the unknown input (the wind force) effect from the fault estimation signal. From the practical point of view, the actuator measurement sensors are corrupted by the sensor measurement noise. An H∞ approach is used based on the unknown input-decoupling observer to minimize the effect of this sensor noise on the fault estimation signal. In order to estimate the multiplicative fault, a fault model modification is used to reform the multiplicative fault into an additive fault representation by which the fault can be estimated. Finally, the proposed design is used to estimate the hydraulic leakage fault occurring in a wind turbine pitch actuator system based on a non-linear benchmark model.

Robust actuator multiplicative fault estimation with unknown input decoupling for a wind turbine system

A model based approach to making an induction motor drive tolerant to intermittent disconnections of the current and voltage sensors is considered. Whilst these are abrupt faults they are hard to detect due to their short duration. It is shown that a simple parity equation method is an obvious approach to diagnosing sensor faults, however the application of model based techniques is actually preferable for achieving reliable fault detection and isolation (FDI) when faced with intermittent faults. The induction motor dynamics have a strongly bi-linear structure. A novel bilinear observer is developed, then extended to produce a scheme for detecting and correcting sensor faults.

Torque and flux estimation for a rail traction system in the presence of intermittent sensor faults

Observer Design for a Class of Non-Linear Systems

An LPV pole-placement approach to friction compensation as an FTC problemThe concept of combining robust fault estimation within a controller system to achieve active Fault Tolerant Control FTC has been the subject of considerable interest in the recent literature. The current study is motivated by the need to develop model-based FTC schemes for systems that have no unique equilibria and are therefore difficult to linearise. Linear Parameter Varying LPV strategies are well suited to model-based control and fault estimation for such systems. This contribution involves pole-placement within suitable LMI regions, guaranteeing both stability and performance of a multi-fault LPV estimator employed within an FTC structure. The proposed design strategy is illustrated using a nonlinear two-link manipulator system with friction forces acting simultaneously at each joint. The friction forces, regarded as a special case of actuator faults, are estimated and their effect is compensated within a polytope controller system, yielding a robust form of active FTC that is easy to apply to real robot systems.

/pdf/an-lpv-pole-placement-approach-to-friction-compensation-as-p7242ftc0n.pdf

Ron J. Patton

Papers

Active FTC for hydraulic pitch system for an off-shore wind turbine

Robust actuator multiplicative fault estimation with unknown input decoupling for a wind turbine system

Torque and flux estimation for a rail traction system in the presence of intermittent sensor faults

Observer Design for a Class of Non-Linear Systems

An LPV pole-placement approach to friction compensation as an FTC problem