3,438 research outputs found
Zonotopic fault detection observer design for Takagi–Sugeno fuzzy systems
This paper considers zonotopic fault detection observer design in the finite-frequency domain for discrete-time Takagi–Sugeno fuzzy systems with unknown but bounded disturbances and measurement noise. We present a novel fault detection observer structure, which is more general than the commonly used Luenberger form. To make the generated residual sensitive to faults and robust against disturbances, we develop a finite-frequency fault detection observer based on generalised Kalman–Yakubovich–Popov lemma and P-radius criterion. The design conditions are expressed in terms of linear matrix inequalities. The major merit of the proposed method is that residual evaluation can be easily implemented via zonotopic approach. Numerical examples are conducted to demonstrate the proposed methodPeer ReviewedPostprint (author's final draft
H ? filtering for stochastic singular fuzzy systems with time-varying delay
This paper considers the H? filtering problem
for stochastic singular fuzzy systems with timevarying
delay. We assume that the state and measurement
are corrupted by stochastic uncertain exogenous
disturbance and that the system dynamic is modeled
by Ito-type stochastic differential equations. Based on
an auxiliary vector and an integral inequality, a set of
delay-dependent sufficient conditions is established,
which ensures that the filtering error system is e?t -
weighted integral input-to-state stable in mean (iISSiM).
A fuzzy filter is designed such that the filtering
error system is impulse-free, e?t -weighted iISSiM and
the H? attenuation level from disturbance to estimation
error is belowa prescribed scalar.Aset of sufficient
conditions for the solvability of the H? filtering problem
is obtained in terms of a new type of Lyapunov
function and a set of linear matrix inequalities. Simulation
examples are provided to illustrate the effectiveness
of the proposed filtering approach developed in
this paper
A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems
This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version
Zonotopic fault estimation filter design for discrete-time descriptor systems
This paper considers actuator-fault estimation for discrete-time descriptor systems with unknown but bounded system disturbance and measurement noise. A zonotopic fault estimation filter is designed based on the analysis of fault detectability indexes. To ensure estimation accuracy, the filter gain in the zonotopic fault estimation filter is optimized through the zonotope minimization. The designed zonotopic filter not only can estimate fault magnitudes, but it also provides fault estimation results in an interval, i.e. the upper and lower bounds of fault magnitudes. Moreover, the proposed fault estimation filter has a non-singular structure and hence is easy to implement. Finally, simulation results are provided to illustrate the effectiveness of the proposed method.Postprint (published version
Recommended from our members
Robust filtering for uncertain linear systems with delayed states and outputs
Copyright [2002] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.Deals with the robust filtering problem for uncertain linear systems with delayed states and outputs. Both time-invariant and time-varying cases are considered. For the time-invariant case, an algebraic Riccati matrix inequality approach is proposed to design a robust H∞ filter such that the filtering process remains asymptotically stable for all admissible uncertainties, and the transfer function from the disturbance inputs to error state outputs satisfies the prespecified H∞ norm upper bound constraint. We establish the conditions under which the desired robust H ∞ filters exist, and derive the explicit expression of these filters. For the time-varying case, we develop a differential Riccati inequality method to design the robust filters. A numerical example is provided to demonstrate the validity of the proposed design approac
Zonotopic unknown input observer of discrete-time descriptor systems for state estimation and robust fault detection
© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This paper studies a set-based unknown input observer based on zonotopes for discrete-time descriptor systems affected by uncertainties with application to state estimation and robust fault detection. In this paper, two types of uncertainties are considered: (i) disturbances and noise both bounded by zonotopes; (ii) unknown inputs that can be decoupled. In terms of different applications, the observer gain for state estimation is designed to minimize the effects of unknown-but-bounded disturbances and noise as well as state estimation errors. On the other hand, for robust fault detection, in addition to attenuating uncertainties, the designed observer gain is also expected to be sensitive to faults. To achieve this goal, we propose an iterative algorithm to design the fault detection gain. Finally, some illustrative results in an application example show the effectiveness of the proposed algorithms.Peer ReviewedPostprint (author's final draft
- …