Non-Asymptotic Kernel-Based Parametric Estimation of Continuous-time

Pin, Gilberto; Assalone, Andrea; Lovera, Marco; Parisini, Thomas

doi:10.1109/tac.2015.2434075

Cited by 24 publications

(40 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Basic concepts and algebra of the Volterra operators (see [19], [22] and the reference therein) are briefly reviewed and some notations are introduced in this section for the reader's convenience.…”

Section: Non-asymptotic Volterra Operators Algebramentioning

confidence: 99%

“…However, in many practical applications characterized by strict requirements on the tracking speed, it is often desirable that the estimation converge to the true location in finite-time. A novel kernelbased approach is first proposed in [19] providing a deadbeat parametric estimation method for continuous-time linear systems. By using Volterra integral operators, this method allows to annihilate the effects of the unknown initial conditions of the states.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Deadbeat Source Localization From Range-Only Measurements: A Robust Kernel-Based Approach

Fedele

et al. 2019

IEEE Trans. Contr. Syst. Technol.

Self Cite

View full text Add to dashboard Cite

Abstract-This paper presents a novel framework for the problem of target localization based on the range information collected by a single mobile agent. The proposed methodology exploits the algebra of Volterra integral operators to annihilate the influence of initial conditions on the transient phase, thus achieving a deadbeat performance. The robustness properties against additive measurement perturbations are analyzed and the bias caused by the time-discretization is characterized as well. Extensive simulation results and comparisons are provided showing the effectiveness of the proposed technique in coping with both stationary and drifting targets.

show abstract

Section: Non-asymptotic Volterra Operators Algebramentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deadbeat Source Localization From Range-Only Measurements: A Robust Kernel-Based Approach

Fedele

et al. 2019

IEEE Trans. Contr. Syst. Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this paper, we resort to a typical linear integral operator (see [22], [35] for more details), defined as…”

Section: A Preliminariesmentioning

confidence: 99%

“…Assuming that the signal ( ) admits the i-th order derivative for ≥ 0 and a kernel ( , ) that admits the i-th order derivative with respect to the second argument, the following relationship holds (obtained by means of the integration by parts [35]):…”

Section: Appendix Amentioning

confidence: 99%

See 1 more Smart Citation

Online Detection of Fundamental and Interharmonics in AC Mains for Parallel Operation of Multiple Grid-Connected Power Converters

Chen

et al. 2018

IEEE Trans. Power Electron.

Self Cite

View full text Add to dashboard Cite

Abstract-Parallel operation of multiple grid-connected power converters through LCL filters is known to have the potential problem of triggering oscillations in the ac mains. Such oscillatory frequencies are not integral multiples of the fundamental frequency and hence form a new source of interharmonics. Early detection of such oscillations is essential for the parallel power converters to move out of the unstable zone. This paper presents an online observer-based algorithm that can perform fast detection of interharmonics within a specified frequency band. The algorithm has been adopted in a specific and reduced form from an integral observer algorithm for detection of fundamental and interharmonic voltage components in the ac mains. A new method based on the kernel signal for fast interharmonic detection is proposed and practically verified. It has been implemented in a digital controller to detect oscillations such as those occurring between two grid-connected power converters. The practical results indicate that the algorithm can locate such frequency within the specific frequency band within 1 mains cycle.

show abstract

Volterra’s kernels-based finite-time parameters estimation of the Chua system

Fedele

D’Alfonso²,

et al. 2018

Applied Mathematics and Computation

Self Cite

View full text Add to dashboard Cite

In this work, the unknown set of parameters of the Chua system is recovered under the hypothesis that the voltages of the capacitors are available. The system is shown to be algebraically observable and identifiable with respect to the well chosen outputs. Focusing on the differential equations, the Volterra kernel-based approach is used to perform an estimation without the uncertainty of the unmeasurable derivatives and the unknown initial conditions.

show abstract

Non-Asymptotic Kernel-Based Parametric Estimation of Continuous-time

Cited by 24 publications

References 13 publications

Deadbeat Source Localization From Range-Only Measurements: A Robust Kernel-Based Approach

Deadbeat Source Localization From Range-Only Measurements: A Robust Kernel-Based Approach

Online Detection of Fundamental and Interharmonics in AC Mains for Parallel Operation of Multiple Grid-Connected Power Converters

Volterra’s kernels-based finite-time parameters estimation of the Chua system

Contact Info

Product

Resources

About