Research Repository

State Feedback Control Against Sensor Faults for Lipschitz Nonlinear Systems via New Sliding Mode Observer Techniques

Liu, Ming, Zhang, Lixian, Shi, Peng and Reza Karimi, Hamid (2011) State Feedback Control Against Sensor Faults for Lipschitz Nonlinear Systems via New Sliding Mode Observer Techniques. In: 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011). IEEE, United States, pp. 7635-7640.

Full text for this resource is not available from the Research Repository.


This paper investigates the problem of simultaneous state and fault estimation and observer-based fault tolerant controller design for Lipschitz nonlinear systems with sensor failure. A new estimation technique is presented in this paper to deal with this design problem. In the proposed approaches, the original system is first augmented by a descriptor model transformation, then a new Proportional and Derivative sliding mode observer technique is developed to obtain accurate estimations of both system states and sensor faults. The designing observer is generalized from the PD observer in [3], but is not a trivial extension. Based on the state estimates, a observer-based control strategy is developed to stabilize the resulting closed-loop system. Finally, a numerical example is presented to illustrate the effectiveness and applicability of the proposed technique.

Item Type: Book Section
ISBN: 9781612848006 (print) 9781612847993 (online)
Additional Information:

Proceedings of a meeting held 12-15 December 2011, Orlando, Florida, USA

Uncontrolled Keywords: ResPubID25056, PD control, closed loop systems, fault diagnosis, nonlinear control systems, observers, sensors, stability, state feedback, variable structure systems
Subjects: Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
Current > FOR Classification > 0802 Computation Theory and Mathematics
Historical > SEO Classification > 970108 Expanding Knowledge in the Information and Computing Sciences
Related URLs:
Depositing User: VUIR
Date Deposited: 22 Mar 2013 05:56
Last Modified: 11 Aug 2020 00:23
ePrint Statistics: View download statistics for this item
Citations in Scopus: 11 - View on Scopus

Repository staff only

View Item View Item

Search Google Scholar