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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., Comment: 12 pages, 5 figures

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., Comment: 15 pages, 6 figures

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. Using eigenfunctions of the Koopman operator for a target nonlinear system, we show that the relative contribution between modes and state variables can be quantified beyond a linear regime, where the nonlinearity of the system is taken into consideration. The proposed contribution factor is applied to the numerical analysis of large-signal simulations for an interconnected AC/multi-terminal DC power system., Comment: 11 pages, 2 figures

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. An architecture for cooperation between transportation and energy management systems is introduced that enables us to design an autonomous Vehicle-to-Grid (V2G) for the provision of multi-objective AS: primary frequency control in a transmission grid and voltage amplitude regulation in a distribution grid connected to EVs. The design is based on the ordinary differential equation model of distribution voltage, which has been recently introduced as a new physics-based model, and is utilized in this paper for assessing and regulating the impact of spatiotemporal charging/charging of a large population of EVs to a distribution grid. Effectiveness of the autonomous V2G design is evaluated with numerical simulations of realistic models for transmission and distribution grids with synthetic operation data on EVs in a sharing service. In addition, we present a hardware-in-the-loop test for evaluating its feasibility in a situation where inevitable latency is involved due to power, control, and communication equipments., Comment: 28 pages, 23 figures

The promising increase of Electric Vehicles (EVs) in our society poses a challenging problem on the impact assessment of their charging/discharging to power distribution grids. This paper addresses the assessment problem in a framework of nonlinear differential equations. Specifically, we address the nonlinear ODE (Ordinary Differential Equation) model for representing the spatial profile of voltage phasor along a distribution feeder, which has been recently introduced in literature. The assessment problem is then formulated as a two-point boundary value problem of the nonlinear ODE model. In this paper we derive an asymptotic charcterisation of solutions of the problem through the standard regular perturbation method. This provides a mathematically-rigor and quantitative method for assessing how the charging/discharging of EVs affects the spatial profile of distribution voltage. Effectiveness of the asymptotic charcterisation is established with simulations of both simple and practical configurations of the power distribution grid., Comment: 23 pages, 8 figures

Koopman mode decomposition (KMD) is a technique of nonlinear time-series analysis capable of decomposing data on complex spatio temporal dynamics into multiple modes oscillating with single frequencies, called the Koopman modes (KMs). We apply KMD to measurement data on oscillatory dynamics of a temperature field inside a room that is a complex phenomenon ubiquitous in our daily lives and has a clear technological motivation in energy-efficient air conditioning. To characterize not only the oscillatory field (scalar field) but also associated heat flux (vector field), we introduce the notion of a temperature gradient using the spatial gradient of a KM. 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., Comment: 8 pages, 5 figures

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. We present a numerical algorithm of KMD based on Gaussian process regression that is capable of handling noisy finite-time data. The algorithm is applied to short-term swing dynamics of a multi-machine power grid in order to estimate oscillatory modes embedded in the dynamics, and thereby the effectiveness of the algorithm is evaluated., Comment: 7 pages, 6 figures, 2019 Japan Joint Automatic Control Conference

We develop an algorithm for synthesizing a spatial pattern of charging/discharging operations of in-vehicle batteries for provision of Ancillary Service (AS) in power distribution grids. The algorithm is based on the ODE (Ordinary Differential Equation) model of distribution voltage that has been recently introduced. In this paper, firstly, we derive analytical solutions of the ODE model for a single straight-line feeder through a partial linearization, thereby providing a physical insight to the impact of spatial EV charging/discharging to the distribution voltage. Second, based on the analytical solutions, we propose an algorithm for determining the values of charging/discharging power (active and reactive) by in-vehicle batteries in the single feeder grid, so that the power demanded as AS (e.g. a regulation signal to distribution system operator for primary frequency control reserve) is provided by EVs, and the deviation of distribution voltage from a nominal value is reduced in the grid. Effectiveness of the algorithm is established with numerical simulations on the single feeder grid and on a realistic feeder grid with multiple bifurcations., Comment: 20 pages, 8 figures

We report a new approach to estimating power system inertia directly from time-series data on power system dynamics. The approach is based on the so-called Koopman Mode Decomposition (KMD) of such dynamic data, which is a nonlinear generalization of linear modal decomposition through spectral analysis of the Koopman operator for nonlinear dynamical systems. The KMD-based approach is thus applicable to dynamic data that evolve in nonlinear regime of power system characteristics. Its effectiveness is numerically evaluated with transient stability simulations of the IEEE New England test system., Comment: 10 pages, 4 figures, conference