Deadbeat source localization from range-only measurements: A robust kernel-based approach

Pin, Gilberto; Parisini, Thomas; Fedele, Giuseppe

doi:10.1109/acc.2016.7525331

Cited by 8 publications

(4 citation statements)

References 19 publications

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“…Another class of finite-time state estimators is described in [25], [26], where Volterra integral operators with suitably designed kernels are used to cancel the effect of unknown initial conditions. Volterra integral operators with tailored kernel functions have been also used to provide combined state-parameter estimates [27], [28]. The use of suitable bivariate kernel functions in place of univariate modulating functions is a key ingredient to enforce internal stability.…”

Section: A a Glimpse On The State Of The Artmentioning

confidence: 99%

Fixed-time Observer Design for LTI Systems by Time-varying Coordinate Transformation

Yang

Serrani

et al. 2020

2020 59th IEEE Conference on Decision and Control (CDC)

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In this work, we present a novel fixed-time state observer for LTI systems based on a time-varying coordinate transformation yielding the cancellation of the effect of the unknown initial conditions from the state estimates. This coordinate transformation allows one to map the state of the original system into that of an auxiliary system that evolves from initial conditions that are known by construction. After a stable observer is designed in the transformed coordinates, an estimate for the state of the original system can be obtained by inverting the above-mentioned map. The invertibility of the map is guaranteed for any time strictly greater than zero, so that the convergence time can be made arbitrarily small in nominal conditions. The robustness of the observer with respect to bounded measurement disturbances is characterized in terms of both transient and norm bounds on the asymptotic stateestimation error. Compared to existing finite and fixed-time approaches, the proposed method does not require high-gain output-error injection, state augmentation, delay operators, or moving-windows. The dimensionality of the observer matches that of the observed system, and its realization takes the form of an LTV system.

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Section: A a Glimpse On The State Of The Artmentioning

confidence: 99%

Fixed-time Observer Design for LTI Systems by Time-varying Coordinate Transformation

Yang

Serrani

et al. 2020

2020 59th IEEE Conference on Decision and Control (CDC)

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“…where ζ 1 (t) and ζ 2 (t) can be exactly estimated while the derivativeζ 2 (t) becomes the main obstacle for detecting and identifying the fault signal promptly and accurately. Inspired by [37], the limited knowledge of the first derivative in ( 24) can be overcome by the Volterra operator with a 1-st order BC-NK, which gives…”

Section: Fault Detection and Isolationmentioning

confidence: 99%

Fast-convergent fault detection and isolation in a class of nonlinear uncertain systems

Boem

2020

European Journal of Control

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The present work proposes a fast-convergent fault detection and isolation (FDI) scheme for linear systems affected by model uncertainties, such as unknown inputs or unbounded nonlinearities. The finite-time convergence is attained by transforming the I/O signals through Volterra operators with suitably designed kernel functions. A novel feature of the proposed approach is the exploitation of a system decomposition that allows removing the effect of intractable uncertainties while recasting the system dynamics in a form applicable for Volterra operators to achieve non-asymptotic estimation. Remarkably, the proposed approach can reconstruct the state variables of the system in an arbitrarily short time and the fault can be diagnosed efficiently by imposing detection and isolation thresholds on transformed signals. The detectability and isolability of the fault are also characterized. The proposed FDI scheme is applied in simulation to a web process system to diagnose the presence of actuator faults. Simulation results confirm the effectiveness of the proposed scheme in two scenarios with nonlinear uncertainties.

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“…To overcome this drawback, a kernel-based deadbeat estimation methodology has been proposed recently in [13] and [19] exploiting Volterra operators that allow to avoid the periodic resetting and high-gain injection showing huge potential in many applications (e.g. [20], [21], [22]).…”

Section: Introductionmentioning

confidence: 99%

Deadbeat Simultaneous Parameter-State Estimation for Linear Continuous-time Systems: a Kernel-based Approach

Boem

et al. 2018

2018 European Control Conference (ECC)

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The simultaneous estimation of parameters and states in continuous-time linear MISO systems is considered in this paper. The estimates of system's parameters and states are provided simultaneously by a single estimator, where Volterra operators are suitably applied to the I/O measurements. This makes the estimator independent on the initial conditions thanks to the design of suitably shaped kernel functions equipped with non-asymptotic properties. As a result, in the noise-free scenario, instantaneous convergence can be obtained. No high-gain injection nor periodic resetting is necessary. Numerical examples are reported showing the effectiveness of the proposed estimator.

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Deadbeat source localization from range-only measurements: A robust kernel-based approach

Cited by 8 publications

References 19 publications

Fixed-time Observer Design for LTI Systems by Time-varying Coordinate Transformation

Fixed-time Observer Design for LTI Systems by Time-varying Coordinate Transformation

Fast-convergent fault detection and isolation in a class of nonlinear uncertain systems

Deadbeat Simultaneous Parameter-State Estimation for Linear Continuous-time Systems: a Kernel-based Approach

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