arXiv subjects

Yoshihiko Susuki

Publications and source records attributed to Yoshihiko Susuki.

At least 19 recordsLinked to original sources

arXiv2026

Experimental Realization of Koopman-Model Predictive Control for an AC-DC Converter

This paper experimentally demonstrates the Koopman-Model Predictive Control (K-MPC) for a real AC-DC converter. The converter is typically modeled with a nonlinear time-variant plant. We introduce a new dynamical approach to lifting measurable dynamics from the plant and constructing a linear time-invariant model that is consistent with control objectives of the converter. We show that the lifting approach, combined with the K-MPC controller, performs well across the full experimental system and outperforms existing control strategies in terms of both steady-state and transient responses.

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arXiv2026

Formal Synthesis of Robust Koopman-Model Predictive Control: A Case Study in AC-DC Power Conversion

This letter proposes a formal synthesis of Robust Koopman-Model Predictive Control (RK-MPC), a novel data-driven approach to formal synthesis of systems with nonlinear dynamics. We formulate a novel optimization problem for RK-MPC by incorporating specifications described by Signal Temporal Logic and prove its closed-loop performance. Effectiveness of the proposed RK-MPC is evaluated by applying it to the reliable design of an AC-DC power converter.

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arXiv2026

e-Traceroute: Physically traceable electricity routing for carbon-free energy utilization

Maximizing the self-consumption of residential photovoltaic generation is a promising pathway to meet urgent decarbonization targets for 2030 (and even for 2035). A viable solution is to create a sharing economy for idle battery capacity within a community. To achieve this, utilizing shared physical assets necessitates complete physical traceability of power flows---the capability to strictly trace the ownership of stored energy among multiple participants. Furthermore, physical traceability is an essential function for demonstrating the use of carbon-free energy resources. Such tracing is impossible in conventional systems owing to two fundamental limitations: the mixing of power flows in a common bus and the decoupling of power and information delivery. This study presents a novel physical-layer technology, called e-Traceroute, that overcomes these limitations and realizes physically traceable electricity exchanges. Specifically, physically distinguishable power routing and data transmission are unified over the same power lines. Prototyping experiments demonstrate successful integration of power transfers and information transactions, validating that the proposed system serves as a physical foundation for a reliable and scalable sharing economy that drives bottom-up decarbonization.

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arXiv2026

An extended Perron-Frobenius operator filter for nonlinear state estimation

We propose an extended Perron--Frobenius Operator Filter (PFOF) for nonlinear state estimation. The method learns the Perron--Frobenius operator, an infinite-dimensional linear operator fully preserving properties of a nonlinear dynamical system, using the extended Dynamic Mode Decomposition (eDMD). This enables us to explicitly account for non-Gaussian distributions exhibited by the nonlinear system within a linear-operator representation, while retaining the freedom to choose basis functions in eDMD. Through two numerical examples, we show that the extended PFOF achieves high computational efficiency and high estimation accuracy by exploiting the flexibility in the choice of basis functions in eDMD.

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arXiv2026

Extracting transient Koopman modes from short-term weather simulations with sparsity-promoting dynamic mode decomposition

Convective features, represented here as warm bubble-like patterns, reveal essential high-level information about how short-term weather dynamics evolve within a high-dimensional state space. In this paper, we introduce a data-driven framework that uncovers transient dynamics captured by Koopman modes responsible for these structures and traces their emergence, growth, and decay. Our approach applies the sparsity-promoting dynamic mode decomposition to weather simulations, yielding a few number of selected modes whose sparse amplitudes highlight dominant transient structures. By tuning the sparsity weight, we balance reconstruction accuracy and model complexity. We illustrate the methodology on weather simulations, using the magnitude of velocity and vorticity fields as distinct observable datasets. The resulting sparse dominant Koopman modes capture the transient evolution of bubble-like pattern and can reduce the dimensionality of weather system model, offering an efficient surrogate for diagnostic and forecasting tasks.

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arXiv2026

On Koopman Resolvents and Frequency Response of Nonlinear Systems

This paper proposes a novel formulation of frequency response for nonlinear systems in the Koopman operator framework. This framework is a promising direction for the analysis and synthesis of systems with nonlinear dynamics based on (linear) Koopman operators. We show that the frequency response of a nonlinear plant is derived through the Laplace transform of the output of the plant, which is a generalization of the classical approach to LTI plants and is guided by the resolvent theory of Koopman operators. The response is a complex-valued function of the driving angular frequency, allowing one to draw the so-called Bode plots, which display the gain and phase characteristics. Sufficient conditions for the existence of the frequency response are presented for three classes of dynamics.

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arXiv2026

Global Linearization of Parameterized Nonlinear Systems with Stable Equilibrium Point Using the Koopman Operator

The Koopman operator framework enables global analysis of nonlinear systems through its inherent linearity. This study aims to clarify spectral properties of the Koopman operators for nonlinear systems with control inputs. To this end, we treat the inputs as parameters throughout this paper. We then introduce the Koopman operator for a parameterized dynamical system with a globally exponentially stable equilibrium point and analyze how eigenfunctions of the operator depend on the parameter. As a main result, we obtain a global linearization, which enables one to transform the nonlinear system into a finite-dimensional linear system, and we show that it depends continuously on the parameter. Subsequently, for a control-affine system, we investigate a condition under which the transformation providing a global bilinearization does not depend on the parameter. This provides the condition under which the global bilinearization for the control-affine system is independent of the parameter.

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arXiv2025

Application of Battery Storage to Switching Predictive Control of Power Distribution Systems Including Road Heating

In regions with heavy snowfall, the living environment is becoming a serious problem due to heavy snow accumulation. A road heating is an electrical device which promotes snow melting by burying a heating cable as a thermal source underground in such regions. When integrating the road heating into power distribution systems, we need to optimize the flow of electric power by appropriately integrating distributed power sources and conventional power distribution equipment. In this paper, we introduce a battery storage to the power distribution system including road heating, and extend the predictive switching control of the systems due to the authors' previous study to the case where battery storage is installed. As a main result, we propose a predictive switching control that utilizes photovoltaic (PV) power generation and surplus power stored in the battery storage effectively, and achieves the reduction of distribution loss, attenuation of voltage fluctuation, and efficient snow melting, simultaneously. We verify the effectiveness of the application of battery storage through numerical simulation using actual time series data of weather conditions and active power of the PV power generation and load.

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arXiv2025

Sparsity-Promoting Dynamic Mode Decomposition Applied to Sea Surface Temperature Fields

In this paper, we leverage Koopman mode decomposition to analyze the nonlinear and high-dimensional climate systems acting on the observed data space. The dynamics of atmospheric systems are assumed to be equation-free, with the linear evolution of observables derived from measured historical long-term time-series data snapshots, such as monthly sea surface temperature records, to construct a purely data-driven climate dynamics. In particular, sparsity-promoting dynamic mode decomposition is exploited to extract the dominant spatial and temporal modes, which are among the most significant coherent structures underlying climate variability, enabling a more efficient, interpretable, and low-dimensional representation of the system dynamics. We hope that the combined use of Koopman modes and sparsity-promoting techniques will provide insights into the significant climate modes, enabling reduced-order modeling of the climate system and offering a potential framework for predicting and controlling weather and climate variability.

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arXiv2025

A Bidirectional Power Router for Traceable Multi-energy Management

To address challenges in improving self-consumption of renewables and resilience in local residential power systems, the earlier work of the authors introduced a novel multi-energy management concept, integrating bidirectional power routing and electricity-hydrogen conversion. This paper focuses on an experimental verification of the bidirectional power router based on line-switching, the essential hardware to realize the concept. The primary contribution is the validation of the router's capability to handle dynamic change of bidirectional power flow. Furthermore, to achieve bidirectional power routing without affecting the smooth and stable operation of the power system, a novel algorithm for router's switching is designed based on power flow monitoring. The effectiveness of the proposed method is demonstrated through an experiment using a setup with a commercially available stationary battery.

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arXiv2024

Koopman Operators for Global Analysis of Hybrid Limit-Cycling Systems: Construction and Spectral Properties

This paper reports a theory of Koopman operators for a class of hybrid dynamical systems with globally asymptotically stable periodic orbits, called hybrid limit-cycling systems. We leverage smooth structures intrinsic to the hybrid dynamical systems, thereby extending the existing theory of Koopman operators for smooth dynamical systems. Rigorous construction of an observable space is carried out to preserve the inherited smooth structures of the hybrid dynamical systems. Complete spectral characterization of the Koopman operators acting on the constructed space is then derived where the existence and uniqueness of their eigenfunctions are ensured. Our results facilitate global analysis of hybrid dynamical systems using the Koopman operator.

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arXiv2024

A System of Bidirectional Power Routing Toward Multi-energy Management

In this paper, we propose a system of bidirectional power routing for inter-house multi-energy management systems that utilize electricity and hydrogen as energy carriers. The key is to share private facilities such as photovoltaic panels and batteries among a group of houses along with a common hydrogen system. A power router of line switching type is introduced as a physical interface to realize the sharing economy between households. The proposed system offers a unique measure to address the urgent challenges of today's multi-energy system, namely increasing the renewables' self-consumption, enhancing the energy system's resilience, and providing traceability of hydrogen in terms of renewability certification. We also present an experimental demonstration under a simplified scenario using prototype hardware.

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arXiv2024

Koopman Analysis of the Singularly-Perturbed van der Pol Oscillator

The Koopman operator framework holds promise for spectral analysis of nonlinear dynamical systems based on linear operators. Eigenvalues and eigenfunctions of the Koopman operator, so-called Koopman eigenvalues and Koopman eigenfunctions, respectively, mirror global properties of the system's flow. In this paper we perform the Koopman analysis of the singularly-perturbed van der Pol system. First, we show the spectral signature depending on singular perturbation: how two Koopman {principal} eigenvalues are ordered and what distinct shapes emerge in their associated Koopman eigenfunctions. Second, we discuss the singular limit of the Koopman operator, which is derived through the concatenation of Koopman operators for the fast and slow subsystems. From the spectral properties of the Koopman operator for the {singularly}-perturbed system and the singular limit, we suggest that the Koopman eigenfunctions inherit geometric properties of the singularly-perturbed system. These results are applicable to general planar singularly-perturbed systems with stable limit cycles.

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arXiv2024

Participation Factors for Nonlinear Autonomous Dynamical Systems in the Koopman Operator Framework

We devise a novel formulation and propose the concept of modal participation factors to nonlinear dynamical systems. The original definition of modal participation factors (or simply participation factors) provides a simple yet effective metric. It finds use in theory and practice, quantifying the interplay between states and modes of oscillation in a linear time-invariant (LTI) system. In this paper, with the Koopman operator framework, we present the results of participation factors for nonlinear dynamical systems with an asymptotically stable equilibrium point or limit cycle. We show that participation factors are defined for the entire domain of attraction, beyond the vicinity of an attractor, where the original definition of participation factors for LTI systems is a special case. Finally, we develop a numerical method to estimate participation factors using time series data from the underlying nonlinear dynamical system. The numerical method can be implemented by leveraging a well-established numerical scheme in the Koopman operator framework called dynamic mode decomposition.

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arXiv2023

Model Predictive Control of Smart Districts Participating in Frequency Regulation Market: A Case Study of Using Heating Network Storage

Flexibility provided by Combined Heat and Power (CHP) units in district heating networks is an important means to cope with increasing penetration of intermittent renewable energy resources, and various methods have been proposed to exploit thermal storage tanks installed in these networks. This paper studies a novel problem motivated by an example of district heating and cooling networks in Japan, where high-temperature steam is used as the heating medium. In steam-based networks, storage tanks are usually absent, and there is a strong need to utilize thermal inertia of the pipeline network as storage. However, this type of use of a heating network directly affects the operating condition of the network, and assuring safety and supply quality at the use side is an open problem. To address this, we formulate a novel control problem to utilize CHP units in frequency regulation market while satisfying physical constraints on a steam network described by a nonlinear model capturing dynamics of heat flows and heat accumulation in the network. Furthermore, a Model Predictive Control (MPC) framework is proposed to solve this problem. By consistently combining several nonlinear control techniques, a computationally efficient MPC controller is obtained and shown to work in real-time.

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arXiv2023

Koopman-Model Predictive Control with Signal Temporal Logic Specifications for Temperature Regulation of a Warm-Water Supply System

Control of warm-water supply for dialysis treatment in a hospital environment is typical of safety-critical control problems. In order to guarantee the continuity of warm-water supply satisfying physical specifications for a wide range of operating conditions, it is inevitable to consider the nonlinearity involved in a dynamic model of a warm-water supply system for the control design. In this paper, we propose to incorporate control specifications described by signal temporal logic, which is a temporal logic with semantics over finite-time signals in formal methods, into the so-called Koopman-Model Predictive Control (MPC) as a novel technique of nonlinear MPC based on the Koopman operator framework for nonlinear systems. This enables us to generate a sequence of optimal inputs such that the controlled state of a nonlinear system can satisfy the specifications. The proposal is applied to the temperature regulation of warm-water supply, and its effectiveness is established numerically.

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arXiv2022

Dissipativity of nonlinear ODE model of distribution voltage profile

In this paper, we consider a power distribution system consisting of a straight feeder line. A nonlinear ordinary differential equation (ODE) model is used to describe the voltage distribution profile over the feeder line. At first, we show the dissipativity of the subsystems corresponding to active and reactive powers. We also show that the dissipation rates of these subsystem coincide with the distribution loss given by a square of current amplitudes. Moreover, the entire distribution system is decomposed into two subsystems corresponding to voltage amplitude and phase. As a main result, we prove the dissipativity of these subsystems based on the decomposition. As a physical interpretation of these results, we clarify that the phenomena related to the gradients of the voltage amplitude and phase are induced in a typical power distribution system from the dissipation equalities. Finally, we discuss a reduction of distribution losses by injecting a linear combination of the active and reactive powers as a control input based on the dissipation rate of the subsystem corresponding to voltage amplitude.

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arXiv2022

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

This paper addresses a control problem on air-conditioning systems in buildings that is regarded as a control practice of nonlinear distributed-parameter systems. Specifically, we consider the design of a controller for suppressing an oscillatory response of in-room temperature field. The main idea in this paper is to apply the emergent theory of Koopman operator and Koopman mode decomposition for nonlinear systems, and to formulate a technique of damping assignment to a nonlinear Koopman mode in a fully data-driven manner. Its effectiveness is examined by numerical simulations guided by measurement of a practical room space.

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