An adaptive observer for uncertain linear time-varying systems with unknown additive perturbations

Pyrkin, Anton A.; Bobtsov, Alexey A.; Isidori, Alberto

doi:10.1016/j.automatica.2022.110677

Cited by 11 publications

(8 citation statements)

References 17 publications

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“…Contrary to [19]- [21], the aim of this study is to guarantee the convergence of the parametric error θ (t) to arbitrarily small neighborhood of zero. In contrast to [17,18], the internal model for δ (t) is unknown.…”

Section: Problem Statementmentioning

confidence: 99%

“…Considering (18), the multiplication of (17) firstly by H ⊤ and then by adj H ⊤ adj {Φ (t)} L 1 yields:…”

Section: A Robust Estimation Of Unknown Parametersmentioning

confidence: 99%

“…However, the uniform upper bound (UUB) of parameter and state estimation errors can be arbitrarily large especially for high-amplitude disturbances. To overcome this drawback, adaptive observers were proposed in [17], [18] on the basis of the internal model principle to parameterize and estimate the unknown perturbations. At the same time, the known perturbation model is a restrictive assumption for practical scenarios.…”

Section: Introductionmentioning

confidence: 99%

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Robust Time-Varying Parameters Estimation Based on I-DREM Procedure

Glushchenko

Lastochkin

2022

IFAC-PapersOnLine

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Section: Problem Statementmentioning

confidence: 99%

“…Considering (18), the multiplication of (17) firstly by H ⊤ and then by adj H ⊤ adj {Φ (t)} L 1 yields:…”

Section: A Robust Estimation Of Unknown Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust Time-Varying Parameters Estimation Based on I-DREM Procedure

Glushchenko

Lastochkin

2022

IFAC-PapersOnLine

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“…In References 12 and 13 the DREM, proposed in Reference 14, is combined with generalized parameter estimation-based observers (GPEBO) 15 to design adaptive observers for LTV systems with delayed measurements and for LTV systems with additive perturbations. 16 Motivated by its application to the gain-scheduled controllers discussed above, attention has been recently centered on the particular problem of adaptive state observers for systems with switching parameters. It should be mentioned that this problem formulation is very closely related to the highly popular scenario of event-triggered control of switching systems.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, several authors have addressed the more challenging problem of adaptive observer design. In References 12 and 13 the DREM, proposed in Reference 14, is combined with generalized parameter estimation‐based observers (GPEBO) 15 to design adaptive observers for LTV systems with delayed measurements and for LTV systems with additive perturbations 16 …”

Section: Introductionmentioning

confidence: 99%

Adaptive state observation of linear time‐varying systems with switching unknown parameters: Application to gain scheduling and event‐triggered control

Romero¹,

Ortega²

2023

Adaptive Control & Signal

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SummaryMotivated by its application in gain scheduling and event‐triggered controllers we propose in this paper an adaptive observer for linear time‐varying (LTV) systems with unknown switching parameters, but known switching time instants. To construct the observer we propose an extension to the generalized parameter estimation‐based observers (GPEBO), which we combine with the least‐squares plus dynamic regression extension and mixing (LS+DREM) estimator recently proposed. We prove that the system state and the parameters converge in finite time inside each switching sub‐interval, under the weak assumption of interval‐excitation (IE). The excellent performance of the proposed observer is illustrated with a practical and an academic example both reported in the literature.

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Zonotopic state estimation and sensor fault detection for a wastewater treatment bioprocess

Zhou,

Wu,

Wang

et al. 2024

Intl J Robust & Nonlinear

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In this paper, a fault diagnosis method for the basic process of microbial growth in wastewater treatment based on interval estimation technology is proposed. First, a nonlinear microbial growth model is converted into a linear time‐varying system. A time‐varying observer is then designed for the generated system, which takes into account an performance. Furthermore, a zonotope‐based set‐membership estimation algorithm is analyzed to synchronize interval estimation operations. In addition, interval residuals are computed from the generated interval state estimation and fault diagnosis is performed for a wastewater treatment bioprocess with sensor fault signals. Finally, the feasibility of the proposed fault diagnosis strategy for the wastewater treatment bioprocess is illustrated through numerical simulations.

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An adaptive observer for uncertain linear time-varying systems with unknown additive perturbations

Cited by 11 publications

References 17 publications

Robust Time-Varying Parameters Estimation Based on I-DREM Procedure

Robust Time-Varying Parameters Estimation Based on I-DREM Procedure

Adaptive state observation of linear time‐varying systems with switching unknown parameters: Application to gain scheduling and event‐triggered control

Zonotopic state estimation and sensor fault detection for a wastewater treatment bioprocess

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