20 research outputs found
Rational interpolation: Modified rational Arnoldi algorithm and Arnoldi-like equations
Published versio
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
Model predictive control based on mixed H2/H∞ control approach for active vibration control of railway vehicles
This paper investigates the application of Model Predictive Control (MPC) technology based on mixed H2/H1 control approach for active
suspension control of a railway vehicle, the aim being to improve the ride quality of the railway vehicle. Comparisons are made with
more conventional control approaches, and the applicability of the linear matrix inequality approach is illustrated via the railway vehicle
example
Mixed-sensitivity approach to H∞ control of power system oscillations employing multiple FACTS devices
This paper demonstrates the enhancement of inter-area mode damping by multiple flexible AC transmission systems (FACTS) devices. Power system damping control design is formulated as an output disturbance rejection problem. A decentralized H∞ damping control design based on the mixed-sensitivity formulation in the linear matrix inequality (LMI) framework is carried out. A systematic procedure for selecting the weights for shaping the open loop plant for control design is suggested. A 16-machine, five-area study system reinforced with a controllable series capacitor (CSC), a static VAr compensator (SVC), and a controllable phase shifter (CPS) at different locations is considered. The controllers designed for these devices are found to effectively damp out inter-area oscillations. The damping performance of the controllers is examined in the frequency and time domains for various operating scenarios. The controllers are found to be robust in the face of varying power-flow patterns, nature of loads, tie-line strengths, and system nonlinearities, including device saturations
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