2017
DOI: 10.1002/rnc.3888
|View full text |Cite
|
Sign up to set email alerts
|

Fault tolerant control of uncertain dynamical systems using interval virtual actuators

Abstract: This is the peer reviewed version of the following article: Rotondo D, Cristofaro A, Johansen TA. Fault tolerant control of uncertain dynamical systems using interval virtual actuators. Int J Robust Nonlinear Control. 2018;28:611–624, which has been published in final form at https://doi.org/10.1002/rnc.3888. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.In this paper, a model reference fault tolerant control strategy based on a reconfigur… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
11
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
3
3
1

Relationship

2
5

Authors

Journals

citations
Cited by 19 publications
(13 citation statements)
references
References 49 publications
0
11
0
Order By: Relevance
“…Let us now consider a jammer which has less available energy to perform the attack, represented by a lower valueτ = 5 s. In this case, Corollary 1 can be applied with α * = 0, α 0 = −40, α 1 = 10, α 2 = 20 and µ 0 = µ 1 = µ 2 = 5, thus allowing for instability of the closed-loop system when even only one of the two actuators is being attacked. For these values, (29) is verified with ∑ n u k=0 ln (µ k ) + α h = −0.17 ≤ 0 (presentation of the symmetric matrices P γ * and virtual actuator gains, which provide feasibility of (30)- (31) and (42), is omitted). For this case, the following scenario will be considered in order to assess the performance of the proposed secure control technique.…”
Section: Numerical Examplementioning
confidence: 99%
See 1 more Smart Citation
“…Let us now consider a jammer which has less available energy to perform the attack, represented by a lower valueτ = 5 s. In this case, Corollary 1 can be applied with α * = 0, α 0 = −40, α 1 = 10, α 2 = 20 and µ 0 = µ 1 = µ 2 = 5, thus allowing for instability of the closed-loop system when even only one of the two actuators is being attacked. For these values, (29) is verified with ∑ n u k=0 ln (µ k ) + α h = −0.17 ≤ 0 (presentation of the symmetric matrices P γ * and virtual actuator gains, which provide feasibility of (30)- (31) and (42), is omitted). For this case, the following scenario will be considered in order to assess the performance of the proposed secure control technique.…”
Section: Numerical Examplementioning
confidence: 99%
“…To this end, the active FTC technique known as virtual actuator might be of interest, since it is based on the idea of performing a reconfiguration of the plant when an unexpected situation occurs, such that the nominal controller can still be used without need of retuning it. Initially proposed for linear time invariant (LTI) systems [34], virtual actuators were later extended to linear parameter varying (LPV) [35,36], hybrid [37], Takagi-Sugeno [38], piecewise affine [39], Hammerstein-Weiner [40], Lipschitz [41] and uncertain [42] systems. Note that the virtual actuator technique belongs to the wider class of fault-hiding reconfiguration approaches, among which there is the dual technique known as virtual sensors, that is employed when the considered faults affect the sensor outputs [43].…”
Section: Introductionmentioning
confidence: 99%
“…Different control methods have been used to deal with external disturbances and faults (see References 1‐18 and the references therein). In Reference 1, an adaptive fault tolerant protocol is proposed for a class of Lipschitz nonlinear systems using adaptive gain technique.…”
Section: Introductionmentioning
confidence: 99%
“…An adaptive integral sliding mode fault tolerant controller is proposed in Reference 13 for nonlinear systems with actuator faults, mismatched disturbance, and time‐varying delay. Interval virtual actuators are designed in Reference 14 for uncertain systems under disturbances and sensor faults with known bounds. Recently, a nonzero‐sum game reinforcement learning based method is developed in Reference 15 to achieve performance optimization for large‐scale industrial processes using only data, which gets rid of the model uncertainties and faults.…”
Section: Introductionmentioning
confidence: 99%
“…This active FTC strategy has been extended successfully to many classes of systems, e.g. linear parameter varying (LPV) systems [26], hybrid systems [27], Takagi-Sugeno systems [28], piecewise affine systems [29] and uncertain systems [30]. To the best of our knowledge, this approach has not been extended yet to descriptor systems, which are often used to model cyber-physical systems and other critical infrastructures, such as water distribution networks [5].…”
Section: Introductionmentioning
confidence: 99%