Search Results for author: Atsushi Ishigame

Found 6 papers, 0 papers with code

Control of Oscillatory Temperature Field in a Building via Damping Assignment to Nonlinear Koopman Mode

no code implementations7 Jul 2022 Yoshihiko Susuki, Kohei Eto, Naoto Hiramatsu, Atsushi Ishigame

This paper addresses a control problem on air-conditioning systems in buildings that is regarded as a control practice of nonlinear distributed-parameter systems.

A mode-in-state contribution factor based on Koopman operator and its application to power system analysis

no code implementations23 May 2022 Kenji Takamichi, Yoshihiko Susuki, Marcos Netto, Atsushi Ishigame

This paper proposes a mode-in-state contribution factor for a class of nonlinear dynamical systems by utilizing spectral properties of the Koopman operator and sensitivity analysis.

Autonomous Vehicle-to-Grid Design for Provision of Frequency Control Ancillary Service and Distribution Voltage Regulation

no code implementations26 Jan 2021 Shota Yumiki, Yoshihiko Susuki, Yuta Oshikubo, Yutaka Ota, Ryo Masegi, Akihiko Kawashima, Atsushi Ishigame, Shinkichi Inagaki, Tatsuya Suzuki

We develop a system-level design for the provision of Ancillary Service (AS) for control of electric power grids by in-vehicle batteries, suitably applied to Electric Vehicles (EVs) operated in a sharing service.

energy management Management

Koopman Mode Decomposition of Oscillatory Temperature Field inside a Room

no code implementations27 Aug 2020 Naoto Hiramatsu, Yoshihiko Susuki, Atsushi Ishigame

By estimating the temperature gradient directly from data, we show that KMD is capable of extracting a distinct structure of the heat flux embedded in the oscillatory temperature field, relevant in terms of air conditioning.

Time Series Time Series Analysis

Application of Gaussian Process Regression to Koopman Mode Decomposition for Noisy Dynamic Data

no code implementations4 Nov 2019 Akitoshi Masuda, Yoshihiko Susuki, Manel Martínez-Ramón, Andrea Mammoli, Atsushi Ishigame

Koopman Mode Decomposition (KMD) is a technique of nonlinear time-series analysis that originates from point spectrum of the Koopman operator defined for an underlying nonlinear dynamical system.

regression Time Series +1

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