Details of a Researcher - Namerikawa, Toru

Papers - Namerikawa, Toru

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Power Demand-Supply Adjustment via Negawatt Trading Based on Regret Matching

Toru Namerikawa

2022 IEEE 61st Conference on Decision and Control (CDC) (IEEE) 2022-December 4394 - 4399 2022.12

Research paper (international conference proceedings), Single Work, Accepted, ISSN 07431546

This study deals with power demand-supply management based on negawatt trading. The aim of this study is to minimize the social cost of negawatt trading and maintain a demand-supply balance. Power consumers and independent system operators participate in the electricity market and each consumer acts based on regret matching, which is one of the learning algorithms. Furthermore, we consider strategy-proofness and individual rationality using VCG mechanism design. In this study, we propose a novel negawatt trading procedure based on regret matching and VCG mechanism design. Finally, the simulation results confirm the effectiveness of the proposed algorithm.

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Cooperative Control of Connected and Automated Vehicles at Signal-free Intersections Considering Passenger Comfort

Akira Kuchiki, Toru Namerikawa

2022 61st Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2022 (IEEE) 909 - 914 2022.09

Research paper (international conference proceedings), Joint Work, Corresponding author, Accepted

In this research, we deal with the coordination problem of Connected and Automated Vehicles (CAVs) at signal-free intersections. First, the problem is formulated to find the appropriate merge time for each CAV. Next, an optimal motion planning problem is formulated to find the control input (jerk) necessary to accurately achieve the given optimal merging time while minimizing the jerk and acceleration. We also present an analytical solution for this motion planning problem with inequality constraints on jerk and acceleration, which achieves both passenger comfort and reduced fuel consumption. Finally, the simulation results show the effectiveness of the proposed method.

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Optimal Incentive Design for One-Way EV Car Sharing System

Shun Sasaki, Toru Namerikawa

2022 IEEE Conference on Control Technology and Applications, CCTA 2022 (IEEE) 851 - 856 2022.08

Research paper (international conference proceedings), Joint Work, Corresponding author, Accepted

This paper deals with an optimal control and scheduling algorithm for one-way car sharing systems. One of the most critical problems of one-way car sharing system is that the parking lots, which tends to be the origins and the destinations, are biased due to the traffic demand of the users, and the cost of relocating the vehicles is becoming high. In order to solve this cost problem, we propose a novel mechanism to give incentives to users in the form of discounts and propose changes to parking lots and departure times to prevent bias in the number of vehicles in parking lots. The optimal parking lot is determined by using a queue information in order to consider the traffic demand distribution of users. Furthermore, an incentive is designed so as to satisfy desirable properties based on VCG mechanism. Finally, the effectiveness of the proposed method is confirmed via several numerical simulations.

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Optimization of fuel consumption and NOx emission for mild HEV via hierarchical model predictive control

Yuka Umezawa, Ken Yamauchi, Hiroki Seto, Toshiro Imamura, Toru Namerikawa

Control Theory and Technology (Springer) 20 ( 2 ) 221 - 234 2022.06

Research paper (scientific journal), Corresponding author, Accepted, ISSN 20956983

In this paper, we consider the fuel economy optimization problem for a mild hybrid electric vehicle (HEV) using hierarchical model predictive control. In the proposed algorithm, two problems are addressed: eco-driving and torque distribution. In the eco-driving problem, vehicle speed was controlled. Considering the reduction in fuel consumption and NOx emissions, the torque required to follow the target speed was calculated. Subsequently, in the torque distribution problem, the distribution between the engine and motor torques were calculated. In this phase, engine characteristics were considered. These problems differ in terms of time scales; therefore, a hierarchical model predictive control is proposed. Lastly, the numerical simulation results demonstrated the efficacy of this research.

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Reducing NOx Emissions and Optimizing Fuel Economy by Controlling Torque and Catalyst Warm-up in Mild HEVs

UMEZAWA Yuka, SETO Hiroki, IMAMURA Toshiro, NAMERIKAWA Toru

ASCC 2022 - 2022 13th Asian Control Conference, Proceedings (IEEE) 59 ( 3 ) 1914 - 1919 2022.05

Research paper (international conference proceedings), Joint Work, Corresponding author, Accepted, ISSN 04534654

In this paper, hierarchical model predictive control is applied to mild HEVs (Hybrid Electric Vehicles) in order to improve fuel economy and reduce NOx emissions. There is a difference in the timescale between the temperature control (high-level) and the torque control (low-level), which are connected via the battery. In high-level of the hierarchical control, the optimal amount of heating from the battery to the catalyst in the exhaust gas after-treatment system is determined. The amount of heating must be determined in a way that the catalyst can optimally purify NOx emitted from the engine. At the low-level of the hierarchical control, the optimal torque distribution for the engine and motor is determined. The controller at both levels then applies model predictive control to consider the future behavior of the HEV's components. Fuel consumption, battery SoC and NOx emissions from the engine are taken into account. Finally, the effectiveness of our proposed method is demonstrated by simulations.

Route Optimization of Mixed Package-Passenger System with Matching Based on Cost Sharing among Passengers

Eri Yamamoto, Toru Namerikawa

ASCC 2022 - 2022 13th Asian Control Conference, Proceedings (IEEE) 2292 - 2297 2022.05

Research paper (international conference proceedings), Joint Work, Corresponding author, Accepted

This paper proposes a route optimization algorithm for a mixed package-passenger system that assigns the task of package delivery to taxicab drivers carrying passengers. The goal is to compensate for the shortage of manpower among package delivery drivers and to reduce CO 2 emissions from delivery vehicles. In this paper, we propose a system that achieves fare reduction for passengers using taxicabs by incorporating stable passenger matching considering the cost sharing among passengers. In addition, we formulate it as a mixed integer linear programming problem to determine the allocation of delivery tasks to taxicab drivers and optimal route. Finally, the effectiveness of the proposed algorithm is shown through numerical simulations.

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Distributed secure state estimation with a priori sparsity information

Takumi Shinohara, and Toru Namerikawa

IET Control Theory & Applications (IET Control Theory and Applications) 16 ( 11 ) 1086 - 1097 2022.04

Research paper (scientific journal), Joint Work, Corresponding author, Accepted, ISSN 17518644

This paper addresses the problem of distributed secure state estimation of a discrete-time linear dynamical system in an adversarial environment. Much of the recent work on this problem has imposed redundancy requirements on measurement and communication networks for state estimation in the presence of attacks. In this paper, the authors aim to relax this redundancy requirement by using prior information about the state to be estimated. A scenario where sparsity information of the state is given is especially considered, and it is shown that the a priori sparsity information alleviates the redundancy requirement. An algorithm for distributed secure state estimation is then derived and a sufficient condition on the convergence of the algorithm is given. Numerical simulations finally illustrate the effectiveness of the algorithm.

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Decentralized Energy Trading Systems for Multiple BEMS Based on Solar Power Generation Forecasting

UMEZAWA Yuka, OKAWA Yoshihiro, NAMERIKAWA Toru

Transactions of the Society of Instrument and Control Engineers (The Society of Instrument and Control Engineers) 58 ( 4 ) 236 - 244 2022.04

Research paper (scientific journal), Joint Work, Corresponding author, Accepted, ISSN 04534654

This paper proposes an optimal trading algorithm for a decentralized energy trading system among multiple building energy management systems (BEMS). Each building generates solar power and has a battery. As a decentralized energy trading algorithm, we first solve the proposed optimization problem to determine the optimal trading volume that minimizes the total purchase price of electricity while satisfying the battery capacity constraint under the consideration of the solar power generation error and the time-varying electricity price. To take into account the foregoing, model predictive control and a scenario-based robust optimization are applied. After the information on the desired amount of electricity transactions is communicated between buildings, the electricity sales price is updated. These steps are iterated until the termination condition is satisfied, and the final trading volume is determined. The convergence of the proposed algorithm is analyzed and the sufficient conditions for the convergence of the price update parameters are shown. Finally, the total price cost and computational cost are compared with the centralized one, and the effectiveness and the superiority of the decentralized control system are shown by several numerical simulations.

Fuel Economy Optimization for mild HEV via Hierarchical Model Predictive Control

YAMAUCHI Ken, UMEZAWA Yuka, SETO Hiroki, IMAMURA Toshiro, NAMERIKAWA Toru

Transactions of the Society of Instrument and Control Engineers (The Society of Instrument and Control Engineers) 58 ( 4 ) 203 - 212 2022.04

Research paper (scientific journal), Joint Work, Corresponding author, Accepted, ISSN 04534654

In this paper, we consider fuel economy optimization problem for mild HEV (Hybrid Electric Vehicle) via hierarchical model predictive control. In our algorithm, we deal with two problems; one is eco-driving, and the other is torque distribution. In the eco-driving problem, we control vehicle speed. Considering the reduction of fuel consumption and NOx emission, we calculate the required torque to follow target speed. Next, in the torque distribution problem, we calculate the distribution between the engine and motor torque. In that phase, engine characteristics are considered. These problems differ in terms of time scales, hence we propose hierarchical model predictive control. Finally, numerical simulation results show the effectiveness of this research.

Carriers Collaboration Routing Optimization of Mixed Cargo and Passenger Vehicles

Eri Yamamoto, Toru Namerikawa

Transactions of the Society of Instrument and Control Engineers (The Society of Instrument and Control Engineers) 58 ( 2 ) 81 - 91 2022.02

Research paper (scientific journal), Joint Work, Corresponding author, Accepted, ISSN 0453-4654

In this paper, we propose a route optimization algorithm for mixed cargo and passenger vehicles by incorporating ridesharing based on matching theory to the delivery planning problem for cargo transportation in order to reduce the total route cost in transportation. First, we consider the cargo-specific delivery route problem, which is formulated as two alternative mixed integer linear programming problems aimed at minimizing the transportation route cost by sharing the delivery tasks among multiple carriers. We then present an algorithm for determining passengers for ridesharing based on stable matching that considers the detour distance of each passenger, describe the passenger travel route search problem based on the cargo transportation route, and propose a series of algorithms for determining the optimal route of mixed cargo and passenger vehicles. Finally, the effectiveness of the proposed algorithm is evaluated through numerical simulations.

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Distributed Partial State Estimation via Virtual Distributed Observers

NAMERIKAWA Ryo, NAMERIKAWA Toru

Transactions of the Society of Instrument and Control Engineers (The Society of Instrument and Control Engineers) 57 ( 11 ) 488 - 498 2021.11

Research paper (scientific journal), Accepted, ISSN 0453-4654

In this paper, we propose virtual distributed observers which are built by virtually excluding some redundant sensors from conventional distributed observers. By using these observers, we can construct not only robust estimators against sensor attacks but detectors of attacks by malicious agents. We also consider the new framework of estimation problem which is more useful to adapt under distributed conditions. This relaxed problem makes it possible to estimate partial state under sensor attacks even if the whole observer system is not detectable. Finally, we confirm the effectiveness of our proposed method through numerical simulations.

Resilient Control of Cyber-Physical System Using Nonlinear Encoding Signal Against System Integrity Attacks

Y Joo, Z Qu, T Namerikawa

IEEE Transactions on Automatic Control 66 ( 9 ) 4334 - 4341 2021.09

Research paper (scientific journal), Joint Work, ISSN 0018-9286

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Robust Voltage Control of a Single-Phase Grid-connected Inverter by H∞ Controller Considering the Load Fluctuation

Yuya Fujie, Kazuhiro Nagira, and Toru Namerikawa

2021 60th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2021 (IEEE) 1215 - 1220 2021.09

Research paper (international conference proceedings), Corresponding author, Accepted

In this paper, we address the new voltage control system of a single-phase grid-connected inverter. In this paper, we apply the standard H∞ control theory and specifically we formulate the voltage control problem as mixed sensitivity problem. By using this method, we can realize both the fastness and robustness of the voltage control under the condition that the uncertainty exists such as fluctuation of the load and the distribution lines. Finally, we confirm the effectiveness of the proposed method through numerical simulation.

Construction of distributed cooperative EMS in multiple homes based on EV state prediction and MPC

小方裕貴，山内賢，滑川徹

電気学会論文誌 C (電子・情報・システム部門誌) (The Institute of Electrical Engineers of Japan) 141 ( 5 ) 685 - 693 2021.05

Research paper (scientific journal), Joint Work, Corresponding author, Accepted, ISSN 0385-4221

In this paper, we propose a novel energy management system (EMS) in which multiple homes cooperate. A buffer with a storage battery is needed to realize efficient power control in response to fluctuations in power demand and supply. Since there are problems such as economic cost and securing of installation place to apply the storage battery, it is conceivable to use electric vehicles (EV) instead. However, EVs need to be charged or discharged at home in preparation for traveling. The purpose of this paper is to propose a distributed cooperative energy management method for multiple homes based on EV state prediction and model predictive control (MPC). Finally, numerical simulation results show the effectiveness of the proposed algorithm.

Cooperative transport control by a multicopter system

Kento Kotani, Zhiqin Guo, Toru Namerikawa, Zhihua Qu

IET Control Theory & Applications (The Institution of Engineering and Technology) 15 ( 6 ) 861 - 876 2021.04

Research paper (scientific journal), Joint Work, Accepted, ISSN 17518644

To date, multicopters have mainly been used in the entertainment and information-gathering fields, but can potentially be used to transport payloads. Specifically, multicopters are more suited for manoeuvring tough terrains and delivering payloads to areas unaccessible by other means. The authors propose a control method to achieve cooperative transport with a plural multicopter system and address the problem of delivering a payload being suspended via cables from multicopters. In cooperative transport using a multicopter system, disturbance (weight, wind, and inertia force) may cause destabilization. A consensus algorithm is used to coordinate flight of helicopters in a formation and to ensure that the payload follows a virtual leader. Disturbances (such as wind and cable tension) are primary causes of destabilization and, in the multicopter setting, they are suppressed by an adaptive robust control, Robust Integral of Sign of the Error control. It is shown that the proposed control design can achieve not only convergence under the ideal setting but also robust operation under significant disturbances. In addition, additional control objectives such as cable tension, payload attitude, and collision avoidance can be integrated and achieved. As an auxiliary method, cable tension control, maintaining a horizontal payload attitude, and collision avoidance are considered. The usefulness of the proposed method was verified by simulations and laboratory flight testing demonstrations.

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Data-Driven Wide-Area Control Design of Power System Using the Passivity Shortage Framework

Y Xu, Z Qu, R Harvey, T Namerikawa

IEEE Transactions on Power Systems (IEEE Transactions on Power Systems) 36 ( 2 ) 830 - 841 2021.03

Research paper (scientific journal), Joint Work, Accepted, ISSN 08858950

A novel wide-area control design is presented to mitigate inter-area power frequency oscillations. A large-scale power system is decomposed into a network of passivity-short subsystems whose nonlinear interconnections have a state-dependent affine form, and by utilizing the passivity shortage framework, a two-level design procedure is developed. At the lower level, any generator control can be viewed as one that makes the generator passivity-short and L-2 stable, and the stability impact of the lower-level control on the overall system can be characterized in terms of two parameters. While the system is nonlinear, the impact parameters can be optimized by solving a data-driven matrix inequality (DMI), and the high-level wide-area control is then designed by solving another Lyapunov matrix inequality in terms of the design parameters. The proposed methodology makes the design modular, and the resulting control is adaptive to operating conditions of the power system. Standard test systems are used to illustrate the proposed design, including DMI and the wide-area control, and simulation results demonstrate its effectiveness in damping out inter-area oscillations.

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Optimal Parking Lot Allocation Using Rematching in Prior Reservation System

NAKAZATO Takuya, NAMERIKAWA Toru

Transactions of the Society of Instrument and Control Engineers (The Society of Instrument and Control Engineers) 57 ( 3 ) 185 - 194 2021.03

Research paper (scientific journal), Joint Work, Corresponding author, Accepted, ISSN 0453-4654

In this paper, we propose a novel Smart Parking System which determines optimal parking lot allocation based on matching theory. In this Smart Parking System, parking lot allocation is determined considering both driver's preference and parking lot manager's preference. Then, there is a possibility that a parking lot allocation is not possible due to no vacant parking space at current time and so on. For the driver who cannot be allocated a parking lot, Prior Reservation System (PRS) conducts the optimal parking lot reallocation considering waiting time of each parking lot until a vacant parking space is available. Also, the driver in PRS is satisfied with individual rationality. So, optimal parking lot allocation including rematching in PRS is determined based on matching theory. Finally, numerical simulation results show the effectiveness of proposed method.

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Incentive Design for One-way Car-sharing Based on Mechanism Design

SASAKI Shun, NAMERIKAWA Toru

Transactions of the Society of Instrument and Control Engineers (The Society of Instrument and Control Engineers) 57 ( 3 ) 168 - 176 2021.03

Research paper (scientific journal), Joint Work, Corresponding author, Accepted, ISSN 0453-4654

This paper proposes a novel car sharing algorithm which changes OD (Origin-Destination) and departure time to the user in exchange for the charge discount, and aims to prevent the bias of the number of vehicles in one-way car-sharing stations. First, a one-way car sharing model based on discrete event systems is described. Next, we will explain how to calculate the optimal combination of the origin, destination, and the departure time in real time, and the method of deciding on incentives that meet strategy-proofness and individual rationality based on mechanism design. Finally, the increase in demand acceptance by the proposed method is confirmed by numerical simulation.

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Self Attack Detection and State Estimation Algorithm in Distributed Observer System under Combination Attack

S Sato, T Namerikawa, Z Qu

2020 59th IEEE Conference on Decision and Control (CDC), 5011-5016 (Proceedings of the IEEE Conference on Decision and Control) 2020-December 5011 - 5016 2020.12

Research paper (international conference proceedings), Joint Work, Corresponding author, Accepted

A problem of attack detection and state estimation in continuous time distributed observer system under combination attack which is defined as in the presence of measurement attack and observer communication attack is considered in this paper. We adopt the notion of virtual state to design an algorithm for attack detection. The algorithm is distributedly used in each local observer and does not need nonlocal information, thus it can be run by only itself. Additionally, we derive the inequality relationship between system graph connectivity and the number of the allowable attacked observer to achieve the detection and estimation with the proposed algorithm as a necessary and sufficient condition. A simple numerical example, finally, illustrates the effectiveness of the proposed algorithm.

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Transient and stability analysis of heterogeneous micro-grid networks subject to uncertainties

Mendoza F.G, Bauso D, Namerikawa T

IET Smart Grid (IET Smart Grid) 3 ( 6 ) 851 - 859 2020.12

Research paper (scientific journal), Joint Work, Accepted

In this study, networks of interconnected heterogeneous micro-grids are studied. The transient dynamics is modelled as an averaging process whereby micro-grids are assimilated to dynamic agents in a network. An analysis of the convergence of the consensus dynamics is carried out under different assumptions on the damping and inertia parameters and the topology of the network. This study provides an insight into the relation between the network topology and the system's response. An analysis of the ways in which the heterogeneous inertial parameters affect the transient response of the network is also implemented. Additionally, the conditions that guarantee stability are identified when the system is under the influence of uncertain non-linear parameters. Finally, simulations are carried out based on a model calibrated on an existing network in the UK under parameter uncertainties.

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