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Kernel-Based Simultaneous Parameter-State Estimation for Continuous-Time Systems

Authors: Peng Li 0024; Francesca Boem; Gilberto Pin; Thomas Parisini;

Kernel-Based Simultaneous Parameter-State Estimation for Continuous-Time Systems

Abstract

In this note, the problem of jointly estimating the state and the parameters of continuous-time systems is addressed. Making use of suitably designed Volterra integral operators, the proposed estimator does not need the availability of timederivatives of the measurable signals and the dependence on the unknown initial conditions is removed. As a result, the estimates converge to the true values in arbitrarily short time in noise-free scenario. In the presence of bounded measurement and process disturbances, the estimation error is shown to be bounded. The numerical implementation aspects are dealt with and extensive simulation results are provides showing the effectiveness of the estimator.

Countries
Italy, Italy, United Kingdom
Keywords

Technology, OBSERVER, Noise measurement, parameter-state joint estimation, 510, Pins, Power systems, Parameter-state estimation, continuous-time systems., Automation & Control Systems, Engineering, 0102 Applied Mathematics, EXCITATION, PERSISTENCY, Science & Technology, IDENTIFICATION, Engineering, Electrical & Electronic, volterra integral operator, Kernel, Fixed-time convergence, 0906 Electrical and Electronic Engineering, Industrial Engineering & Automation, Electrical & Electronic, Convergence, Estimation, Simulation, 0913 Mechanical Engineering

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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