Fault detection and isolation filter design for systems subject to polytopic uncertainties

This paper considers the robust fault detection and isolation (FDI) problem for linear time-invariant dynamic systems subject to faults, disturbances and polytopic uncertainties. We employ an observer-based FDI filter to generate a residual signal. We propose a cost function that penalizes a weighted combination of the deviation of the fault to residual dynamics from a given fault isolation reference model, as well as the effects of disturbances and uncertainties on the residual, using the Hinfin norm as a measure. The proposed cost function thus captures the requirements of fault detection and isolation and disturbance rejection in the presence of polytopic uncertainties. We derive necessary and sufficient conditions for the existence of an FDI filter that achieves the design specifications. This condition takes the form of easily implementable linear matrix inequality (LMI) optimization problem

Integrated design of dynamic controller with fault diagnosis and tolerance

Fault detection capability tends to become an integral part of control system design procedures for practical engineering systems. It is thus desirable fault diagnosis/tolerance functions to also be included in the controller design. In this context, we develop a generic observer-based feedback controller where the observer-part can also generate a residual signal for fault detection purposes. The design objectives is a mixture of Hinfin control and Hinfin fault detection and isolation. This multi-objective optimization problem is then formulated using Bilinear Matrix Inequalities (BMI) and a sub-optimal solution is achieved via transformation to Linear Matrix Inequalities (LMI). The developed approach and algorithm are verified in study of an application to a railway suspension system of ride quality maintenance

Fault detection and isolation filter design for systems subject to polytopic uncertainties

This paper considers the robust fault detection and isolation (FDI) problem for linear time-invariant dynamic systems subject to faults, disturbances and polytopic uncertainties. We employ an observer-based FDI filter to generate a residual signal. We propose a cost function that penalizes a weighted combination of the deviation of the fault to residual dynamics from a given fault isolation reference model, as well as the effects of disturbances and uncertainties on the residual, using the Hinfin norm as a measure. The proposed cost function thus captures the requirements of fault detection and isolation and disturbance rejection in the presence of polytopic uncertainties. We derive necessary and sufficient conditions for the existence of an FDI filter that achieves the design specifications. This condition takes the form of easily implementable linear matrix inequality (LMI) optimization problem

Integrated design of dynamic controller with fault diagnosis and tolerance

Fault detection capability tends to become an integral part of control system design procedures for practical engineering systems. It is thus desirable fault diagnosis/tolerance functions to also be included in the controller design. In this context, we develop a generic observer-based feedback controller where the observer-part can also generate a residual signal for fault detection purposes. The design objectives is a mixture of Hinfin control and Hinfin fault detection and isolation. This multi-objective optimization problem is then formulated using Bilinear Matrix Inequalities (BMI) and a sub-optimal solution is achieved via transformation to Linear Matrix Inequalities (LMI). The developed approach and algorithm are verified in study of an application to a railway suspension system of ride quality maintenance

Output selection with fault tolerance via dynamic controller design

Input-Output selection/placement for control systems has been an attractive research topic in particular under fault-free conditions. In this paper we present a methodology of output selection in a closed-loop framework with a view of fault tolerance capability. The principles with regards to the selection of sensors are reduced hardware redundancy, reduced costs and easier implementation, and acceptable degraded performance when faults occur. The selection of sensors is based upon both closed-loop control and fault tolerance objectives by solving an H-infinity optimization problem for each group of sensors sets via Linear Matrix Inequalities (LMIs). The proposed scheme is applied to a practical example of ride quality improvement of a high speed rail vehicle.</p

Additional file 1: of Epigenetic silencing of a long non-coding RNA KIAA0495 in multiple myeloma

Materials and methods. (DOCX 20 kb

Output selection under control and fault detectability considerations

In a variety of practical engineering systems, i.e. aerospace, mechanical systems, railway vehicle systems, for a given requirement the range of possible locations for sensors is usually known, with the practical engineering issue of optimizing their location. Input-Output selection/placement for control systems has been widely researched in particular under fault-free conditions. In this paper we discuss on the feasibility of an (output) sensor selection scheme in a closed-loop framework based on both control performance and fault detectability metrics. The selection of sensors is based upon both closed-loop control and fault detection objectives by solving a mixed H−/H∞ optimization problem for each group of sensors available via Linear Matrix Inequalities (LMI). The efficacy of the scheme is illustrated via a numerical example