State estimation based on multirate Kalman filter for power systems driven by switching inverter

Hiroki Kurumatani, Seiichiro Katsura

Research output: Contribution to journalArticle

Abstract

This paper presents a design methodology of a Kalman filter for a multirate control system with a fast input system. There are many applications whose sensory system is slower than the input system in a power system. The sensory system is required to perform fast sensing while ensuring a low signal-to-noise ratio, although it requires additional time compared with that of a low-resolution converter. The Kalman filter is an effective tool in such a situation and it estimates parameters while eliminating noise. Because the optimality of this filter is ensured when the system model and noise variance on the system are well identified, rigorous discretization should be considered on the multirate control system. With this in mind, the paper presents the design method of a multirate Kalman filter as is the case for a single-rate controller. Further, the noise variance and oversampling ratio of the multirate controller is confirmed using the Monte Carlo method. Numerical simulation of a voltage inverter theoretically validates the design methodology.

Original languageEnglish
Pages (from-to)231-239
Number of pages9
JournalIEEJ Journal of Industry Applications
Volume8
Issue number2
DOIs
Publication statusPublished - 2019 Jan 1

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State estimation
Kalman filters
Control systems
Controllers
Signal to noise ratio
Monte Carlo methods
Computer simulation
Electric potential

Keywords

  • Kalman filter
  • Multirate system
  • Power electronics

ASJC Scopus subject areas

  • Automotive Engineering
  • Energy Engineering and Power Technology
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

Cite this

State estimation based on multirate Kalman filter for power systems driven by switching inverter. / Kurumatani, Hiroki; Katsura, Seiichiro.

In: IEEJ Journal of Industry Applications, Vol. 8, No. 2, 01.01.2019, p. 231-239.

Research output: Contribution to journalArticle

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