Details of a Researcher - Namerikawa, Toru

Presentations -

Division display 21 - 40 of about 184 ／ All the affair displays >>

Regional demand-supply management based on dynamic pricing in multi-period energy market

Yoshihiro Okawa and Toru NAMERIKAWA

Proc. of IEEE Conference on Decision and Control,

2015.12

Oral presentation (general)

This paper deals with a regional demand response method based on dynamic electricity pricing in a multi-period energy market. In the proposed method, first, the power demand and supply in each area are determined considering power flow using the retail and wholesale electricity prices in a day-ahead market. Next, to adjust for power deviations caused by errors in power generation, our proposed method solves the problem of optimal allocation between power demand reduction by consumers and increased power supply from balancing generators in a real-time market. This paper also shows a distributed algorithm for obtaining the optimal values of each market player in both the day-ahead and real-time markets, and finally, numerical simulation results demonstrate the effectiveness of the proposed method.

LMI-based Formation Control Considering Disconnection of Network Links for a Multi-UAV system

Shouhei Mori and Toru NAMERIKAWA

SWARM 2015: The First International Symposium on Swarm Behavior and Bio-Inspired Robotics,

2015.10

Oral presentation (general)

Flocking Control of a Leader-follower System considering Connectivity Maintenance

Itazuri Kazuki and Toru NAMERIKAWA

SWARM 2015 : The First International Symposium on Swarm Behavior and Bio-Inspired Robotics,

2015.10

Oral presentation (general)

The paper deals with a leader-follower flocking control for a multi-agent system which consists of multiple
agents and a leader. The proposed method enables all agents to be disposed at an uniform distance, reach agreement on a
same velocity with their neighborhood, and to track a moving leader independently. Leader is seen as one of the agents,
in addition, all agents obtain their goal using their neighborhood information only. Furthermore, we suggest the bounded
potential function to guarantee the collision avoidance and connectivity maintenance between the agents. As a result, all
of the swarm can move with preserving flocking configuration. Finally, numerical simulations show the effectiveness of
the proposed method.

Image-based Position Estimation of UAV using Kalman Filter

Takaaki Kojima and Toru Namerikawa

Proceedings of 2015 IEEE Conference on Control Applications,

2015.09

Oral presentation (general)

This paper deals with the position estimation
problem by using the Kalman Filter with compensations for
unexpected observations. In the position estimation problem,
robot observations sometimes yield unexpected values, resulting
in the deterioration of the estimation accuracy. For example,
visual observation with an unmanned aerial vehicle often yields
unexpected results because of blurred images. In this paper,
we propose a method to assigns weights to the observations
in order to remove the effects of unexpected observations. In
the proposed method, unexpected observations are detected by
comparing the observation values with its estimates; the weights
of these observations are then determined. On the basis of
simulation and experimental results, we demonstrate that a
robot’s position can be estimated by the proposed method.

Unscented Kalman filter for position estimation of UAV by using image information

Tang Swee Ho, Kojima Takaaki, Namerikawa Toru, Yeong Che Fai, Su Eileen Lee Ming

Proceedings of SICE Annual conference,

2015.07

Oral presentation (general)

In this paper, the position estimation problem is solved by using unscented Kalman filter with observation uncertainty's compensations. These observation uncertainties causing the estimation become inaccurate in position estimate problem. Visual observation is difficult for an unmanned aerial vehicle equipped with only a monocular-vision camera and often results in observation error because of the detected blurred images. A method to weight the observations is proposed in order to improve the position estimation. Simulation is performed using MATLAB and Simulink to verify the proposed method. The simulation result shows that the proposed method can estimate the position accurately.

Distributed dynamic pricing with alternating decision making of market players

Okawa Yoshihiro, Namerikawa Toru

Proceedings of SICE Annual conference,

2015.07

Oral presentation (general)

This paper deals with a distributed decision procedure for determining the electricity price for a future smart grid. In order to derive the optimal regional prices and improve the convergence speed of the algorithm without private information of market players, we propose a price decision algorithm with an alternating decision making of market players. In this paper, we show that the optimal regional prices derived by using our proposed algorithm maximize the social welfare of power networks which includes profits of power consumers and power suppliers with renewable energy generators. Also, we discuss the convergence property of the proposed price decision algorithm. Finally, the feasibility of our proposed dynamic pricing methodology is shown with numerical simulation results.

Formation Control with Collision Avoidance for a Multi-UAV System using Decentralized MPC and Consensus-based Control

Yasuhiro Kuriki and Toru Namerikawa

Proceedings of the 14th European Control Conference,

2015.07

Oral presentation (general)

In this paper, we propose a cooperative formation
control strategy with collision-avoidance capability for a multi-unmanned aerial vehicle (UAV) system by using decentralized model predictive control (MPC) and consensus-based control. Each of the UAVs plans only its own action to track a trajectory. The trajectory is planned for desired formation flying using a consensus-based control algorithm. Collision-avoidance is regarded as coupled constraints. We show how the optimization problems with collision-avoidance can be solved by each UAV in parallel with the other UAVs so that decisions taken independently by each UAV can ensure consistency with the coupled constraints of collision-avoidance. In addition, we show that our proposed approach hardly affects the computation time to solve the optimization problems with collision-avoidance compared to the time for solving the problems without collision-avoidance. Finally, the proposed approach is validated by simulations.

Decentralized Fault Detection of Multiple Cyber Attacks in Power Network via Kalman Filter

Takashi Irita and Toru Namerikawa

Proceedings of the 14th European Control Conference,

2015.07

Oral presentation (general)

This paper discusses faults diagnosis method of multiple cyber attacks in networked electrical power systems. We deal with a power network of a centralized system, and then, some parameters are estimated by Kalman filter. Using a sensor network system, each of sensor nodes can exchange
information by wireless communication. A fault diagnosis
method is proposed by using both fault detection diagnosis
matrix and fault distinction matrix. The former is composed
of estimated values and observed values. On the other hand,
the latter is composed of observed values and calculated values via the senor network. Finally, the effectiveness of the proposed approach is validated by a simulation experiment.

Dynamic Electricity Pricing via the H-infinity Control Considering Uncertainties in Market Participants' Behavior

Yoshihiro Okawa and Toru Namerikawa

Proceedings of the 14th European Control Conference,

2015.07

Oral presentation (general)

This paper deals with a dynamic pricing via the
H-infinity control considering uncertainties in market participants' behavior. The dynamic pricing is a decision procedure of an electricity price based on power demand and supply information from selfish power consumers and generators. However, since market participants have uncertainties in their behavior, the price decision procedure is required to have robustness
against these uncertainties for stable operation of power systems. Then, in this paper, we propose a novel price decision procedure via the H-infinity control and also show the effectiveness of our proposed price decision method in simulation results.

Power system stabilization by direct load control based on strategy-proofness and individual rationality

Sato Ryutaro, Namerikawa Toru

Proceedings of American Control Conference,

2015.07

Oral presentation (general)

This paper proposes a novel direct load control method to stabilize the system frequency. The proposed method utilizes the consumers' controllable loads for load frequency control. By solving an optimization problem to maximize the social welfare function, the input required for the frequency control is allocated among the controllable loads and the load frequency control generator in an economically rational manner. To introduce the direct control program for smooth operation of the power system, preventing consumers from cheating and guaranteeing their benefits are required. Thus, strategy-proofness and individual rationality based on the Groves and Clarke mechanism were used to design the electricity charge. Each consumer bids on the utility functions truthfully to the independent system operator and gains from participating in the proposed direct load control program. The effectiveness of the proposed method was demonstrated through numerical simulations.

Short-Term Wind Power Prediction via Kalman Filter

Tomoki ishikawa and Toru Namerikawa

Proceedings of IEEJ International Workshop on Sensing, Actuation, and Motion Control,

2015.03

Oral presentation (general)

This paper addresses wind power prediction which is known to be a key technology in EMS(Energy Management
Systems). In this paper, 24 hours ahead power prediction method using a filtering theory is proposed for wind power
generation. The prediction method is a simple algorithm, the procedure of prediction consists of two steps, the data
processing and the calculation of predicted values. In the calculation of predicted value, the unknown parameters are
estimated via constrained kalman filter. Moreover, in the estimation of the unknown parameters, the convergence of
them are also guaranteed. Finally, the advantages of the proposed method over the conventional method are shown
through actual prediction evaluations.

Short-Term Wind Power Prediction via Kalman Filter

ISHIKAWA TomokiNAMERIKAWA Toru

IEEJ International Workshop on Sensing, Actuation, and Motion Control (Nagoya, Japan) ,

2015.03

Oral presentation (general)

This paper addresses wind power prediction which is known to be a key technology in EMS(Energy Management
Systems). In recent years, an introductory expansion of renewable energy is expected and the prediction of
wind power generation is needed for taking in wind power generation. The goal of this work is to predict the amount
of generation in the next day from the past actual data and the weather forecast data of wind. In this paper, 24 hours
ahead power prediction method using a filtering theory is proposed for wind power generation. The prediction method
is a simple algorithm, the procedure of prediction consists of two steps, the data processing and the calculation of predicted values. In the data processing, in order to get the correlative data from the database, we employ JIT(Just-In-Time)
Modeling. In the calculation of predicted value, we provide the regression model for wind speed and wind power, and the
unknown parameters are estimated via constrained kalman filter. Finally, the advantages of the proposed method over the conventional method are shown through simulations.

エネルギーネットワークの分散協調制御

NAMERIKAWA Toru

第2回制御部門マルチシンポジウム (東京電機大学) ,

2015.03

Oral presentation (invited, special)

本講演では，エネルギーネットワークシステムの分散的管理・制御問題に対して，分散協調制御理論からのアプローチとして，講演者のこれまでの一連の研究成果を紹介する．具体的にはスマートグリッドの分散制御，電力市場における分散的最適価格設定法と需給制御，スマートグリッドの最適エネルギーマネジメントに関して議論するとともに，その基盤となる協調制御，分散制御に関する過去の研究についても言及する．最後に今後の研究の展望と将来の方向性を述べる．

Experimental Validation of Cooperative Formation Control with Collision Avoidance for a Multi-UAV System

KURIKI YasuhiroNAMERIKAWA Toru

Proceedings of the 6th International Conference on Automation, Robotics and Applications, 2015 (Queenstown, New Zealand) ,

2015.02

Oral presentation (general)

In this study, we consider cooperative control
issues for a multi-unmanned aerial vehicle (UAV) system.
Specifically, we present a cooperative formation control strategy for a multi-UAV system with unidirectional network links. Our strategy is to apply a consensus-based algorithm and leaderfollower structure to the UAVs so that they can cooperatively fly in formation. The leader provides each UAV with commands to generate a geometric configuration of the formation. Convergence is guaranteed when the cooperative formation control algorithm is applied to the UAVs. Collisions among UAVs can occur when they are flying with the cooperative control UAVs.
Our strategy for collision avoidance is to apply an artificial potential approach to the UAVs. Experiments are performed on multiple commercial small UAVs to validate the proposed formation control algorithm with collision-avoidance capability.

Dynamic pricing considering constraints of power grids

Okawa Yoshihiro, Namerikawa Toru

Proceedings of SICE Annual Conference,

2014.10

Oral presentation (general)

This paper deals with a model of a real-time electricity market for a smart grid, and discusses how to decide wholesale and retail prices of electricity among market participants: power consumers, power suppliers and an independent system operator. In this paper, we consider a linearized AC model of a power grid with a direct current process and show that the wholesale price for suppliers is determined as the optimal Lagrange multiplier corresponding to the nodal power balance constraints. In addition, we propose a decision procedure for the retail pricing of electricity for consumers. In order to improve the convergence speed of the algorithm, we apply the iterative gradient method with line search to a retail pricing decision procedure, in which the optimal step size is determined in each iteration step. Simulation results, finally, show the effectiveness of the proposed retail pricing decision procedure.

Fuel consumption optimization for a power-split HEV via gain-scheduled model predictive control

Iyama Hitoshi, Namerikawa Toru

Proceedings of SICE Annual Conference,

2014.10

Oral presentation (general)

In this paper, we propose a fuel consumption optimization technique for a power-split hybrid electric vehicle (HEV) via gain-scheduled model predictive control. The control algorithms for the hybrid powertrain choose the power split between the internal combustion engine and electric motor of the HEV in order to minimize the fuel consumption. The operating conditions of the HEV change during driving in real time by road conditions and driver demand. Therefore, it is necessary to have optimal control in real time and to consider the time-varying motor condition. We model an HEV and propose a gain-scheduled model predictive control for a power-split HEV. Using the proposed technique, the optimal fuel consumption for a power-split HEV is achieved. Finally, the proposed approach is validated by numerical simulations.

Hierarchical Control of Power Networks by using Overlapping Information

SUEHIRO TomoharuNAMERIKAWA Toru

14th International Conference on Control, Automation and Systems (ICCAS 2014) (KINTEX, Gyeonggi-do, Korea) ,

2014.10

Oral presentation (general)

This study deals with decentralized and hierarchical control for electric power networks by using overlapping
information. The control objective is to minimize the cost function of the load frequency control problem. The control
law consists of three steps. We apply the decentralized hierarchical control methodology to large-scale electrical power networks consisting of distributed power storage and generation sources such as batteries and wind power generators. Through several numerical simulation results of decentralized power networks, we verified their stability, compared the proposed and the previous decentralized methods, and showed the effectiveness of the proposed method.

Fuel Consumption Optimization for a Power-Split HEV via Gain-Scheduled Model Predictive Control

IYAMA HitoshiNAMERIKAWA Toru

SICE Annual Conference 2014 (Hokkaido University, Sapporo, Japan) ,

2014.09

Oral presentation (general)

In this paper, we propose a fuel consumption optimization technique for a power-split hybrid electric vehicle
(HEV) via gain-scheduled model predictive control. The control algorithms for the hybrid powertrain choose the power split between the internal combustion engine and electric motor of the HEV in order to minimize the fuel consumption.
The operating conditions of the HEV change during driving in real time by road conditions and driver demand. Therefore, it is necessary to have optimal control in real time and to consider the time-varying motor condition. We model an HEV and propose a gain-scheduled model predictive control for a power-split HEV. Using the proposed technique, the optimal fuel consumption for a power-split HEV is achieved. Finally, the proposed approach is validated by numerical simulations.

Dynamic Pricing Considering Constraints of Power Grids

OKAWA YoshihiroNAMERIKAWA Toru

SICE Annual Conference 2014 (Hokkaido University, Sapporo, Japan) ,

2014.09

Oral presentation (general)

This paper deals with a model of a real-time electricity market for a smart grid, and discusses how to decide
wholesale and retail prices of electricity among market participants: power consumers, power suppliers and an independent system operator. In this paper, we consider a linearized AC model of a power grid with a direct current process and show that the wholesale price for suppliers is determined as the optimal Lagrange multiplier corresponding to the nodal power balance constraints. In addition, we propose a decision procedure for the retail pricing of electricity for consumers.
In order to improve the convergence speed of the algorithm, we apply the iterative gradient method with line search to a
retail pricing decision procedure, in which the optimal step size is determined in each iteration step. Simulation results, finally, show the effectiveness of the proposed retail pricing decision procedure.

Consensus-based Cooperative Formation Control with Collision Avoidance for a Multi-UAV System

KURIKI YasuhiroNAMERIKAWA Toru

The 2014 American Control Conference, Portland, USA (ACC2014) (Portland, USA) ,

2014.06

Oral presentation (general)

In this paper, we study cooperative control problems
with a multi-UAV system. Specifically, we propose a c
consensus-based cooperative formation control strategy with
collision-avoidance capability for a group of multiple unmanned aerial vehicles (UAVs). To cooperatively fly in formation, a consensus-based algorithm and a leader-follower structure are applied to the UAVs. Collisions among the UAVs can occur while they are flying with the cooperative control algorithm.
Therefore, we describe how the cooperatively controlled UAVs
avoid collisions while they are flying to desired position for formation. The collision-avoidance strategy is based on an artificial potential approach. The convergence is guaranteed even when the cooperative formation control algorithm and the collision-avoidance control algorithm are simultaneously applied to the quadrotors. Finally, the proposed approach is validated by some simulations.

　 Previous page - Next page 　