Description |
1 online resource |
Series |
Springer theses |
|
Springer theses.
|
Contents |
Introduction.- Part -- Advances in gain-scheduling techniques -- Background on gain-scheduling.- Automated generation and comparison of Takagi-Sugeno and polytopic quasi-LPV models -- Robust state-feedback control of uncertain LPV systems.- Shifting state-feedback control of LPV systems -- part 2 -- Background on fault tolerant control.- Fault tolerant control of LPV systems using robust state-feedback control.- Fault tolerant control of LPV systems using reconfigured reference model and virtual actuators -- Fault tolerant control of unstable LPV systems subject to actuator saturations and fault isolation delay -- Conclusions and future work |
Summary |
This thesis reports on novel methods for gain-scheduling and fault tolerant control (FTC). It begins by analyzing the connection between the linear parameter varying (LPV) and Takagi-Sugeno (TS) paradigms. This is then followed by a detailed description of the design of robust and shifting state-feedback controllers for these systems. Furthermore, it presents two approaches to fault-tolerant control: the first is based on a robust polytopic controller design, while the second involves a reconfiguration of the reference model and the addition of virtual actuators into the loop. In short, the thesis offers a thorough review of the state-of-the art in gain scheduling and fault-tolerant control, with a special emphasis on LPV and TS systems |
Bibliography |
Includes bibliographical references |
Notes |
"Doctoral thesis accepted by Universitat Politècnica de Catalunya, Barcelona, Spain." |
|
Online resource; title from PDF title page (EBSCO, viewed October 25, 2017) |
Subject |
Fault tolerance (Engineering)
|
|
Feedback control systems.
|
|
TECHNOLOGY & ENGINEERING -- Engineering (General)
|
|
TECHNOLOGY & ENGINEERING -- Reference.
|
|
Fault tolerance (Engineering)
|
|
Feedback control systems
|
Form |
Electronic book
|
ISBN |
9783319629025 |
|
3319629026 |
|
331987425X |
|
9783319874258 |
|