A subspace algorithm for simultaneous identification and input reconstruction

Palanthandalam-Madapusi, Harish J.; Bernstein, Dennis S.

doi:10.1002/acs.1057

Cited by 27 publications

(1 citation statement)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recall that system ( 6) is invertible with respect to the input/output pair (f, γ 2 ). This property lets us tackle the input reconstruction by means of inversion of the discrete-time dynamics [10], [21]. As this amounts to solving a least squares problem on a finite time window, the reconstruction is deadbeat [10].…”

Section: B Fault Estimationmentioning

confidence: 99%

Joint State, Disturbance and Fault Estimation for Weakly Output Redundant Discrete-Time Linear Systems

Yang

Barboni

Rezaee

et al. 2022

2022 IEEE 61st Conference on Decision and Control (CDC)

View full text Add to dashboard Cite

The problem considered in this paper is dual to the control problem for over-actuated systems found in the literature. We show that, due to a certain notion of weak output redundancy, there always exists an unobservability subspace containing the input subspace, which ensures that the original system can be partitioned into two subsystems, one of which is not affected by actuator faults. We use this fact to estimate the disturbance and the fault in a cascaded fashion: we first design a discrete-time filter on a properly designed residual signal, that can reconstruct the disturbance. The estimated disturbance can then be used to perform fault detection and estimation in a cascaded fashion. A numerical example verifies the efficacy of the proposed strategy.

show abstract

Section: B Fault Estimationmentioning

confidence: 99%

Joint State, Disturbance and Fault Estimation for Weakly Output Redundant Discrete-Time Linear Systems

Yang

Barboni

Rezaee

et al. 2022

2022 IEEE 61st Conference on Decision and Control (CDC)

View full text Add to dashboard Cite

show abstract

l-Delay Input and Initial-State Reconstruction for Discrete-Time Linear Systems

Kirtikar

Palanthandalam-Madapusi

Zattoni

et al. 2010

Circuits Syst Signal Process

Self Cite

View full text Add to dashboard Cite

Prior results on input reconstruction for multi-input, multi-output discretetime linear systems are extended by defining l-delay input and initial-state observability. This property provides the foundation for reconstructing both unknown inputs and unknown initial conditions, and thus is a stronger notion than l-delay left invertibility, which allows input reconstruction only when the initial state is known. These properties are linked by the main result (Theorem 4), which states that a MIMO discrete-time linear system with at least as many outputs as inputs is l-delay input and initial-state observable if and only if it is l-delay left invertible and has no invariant zeros. In addition, we prove that the minimal delay for input and state reconstruction is identical to the minimal delay for left invertibility. When transmission zeros are present, we numerically demonstrate l-delay input and state reconstruction to show how the input-reconstruction error depends on the locations of the zeros. Specifically, minimum-phase zeros give rise to decaying input reconstruction error, nonminimumphase zeros give rise to growing reconstruction error, and zeros on the unit circle give rise to persistent reconstruction error.

show abstract

Deadbeat unknown-input state estimation and input reconstruction for linear discrete-time systems

Ansari

Bernstein

2019

Automatica

View full text Add to dashboard Cite

A subspace algorithm for simultaneous identification and input reconstruction

Cited by 27 publications

References 40 publications

Joint State, Disturbance and Fault Estimation for Weakly Output Redundant Discrete-Time Linear Systems

Joint State, Disturbance and Fault Estimation for Weakly Output Redundant Discrete-Time Linear Systems

l-Delay Input and Initial-State Reconstruction for Discrete-Time Linear Systems

Deadbeat unknown-input state estimation and input reconstruction for linear discrete-time systems

Contact Info

Product

Resources

About