Papers by Toru Namerikawa
Carriers Collaboration Routing Optimization of Mixed Cargo and Passenger Vehicles Based on Stable Matching
Transactions of the Society of Instrument and Control Engineers, 2022
Keisoku Jidō Seigyo Gakkai ronbunshū, 2016
In this paper, we study detection problem of replay attacks on smart grid. A smart grid is operat... more In this paper, we study detection problem of replay attacks on smart grid. A smart grid is operated as if it is a Cyber-Physical System with solid links between its calculation and its material constituents, hence ensuring cyber security has been an important role. The goal of this paper is to detect replay attack that is one of cyber attacks on the sensors of a control system. We propose a detecting method adding intentional noise to not only sensors as code signal but also input. Replay attack can immediately be reflected by using fault diagnosis matrices that are composed of the estimator and observed values even if code signal is decrypted. Finally, we show simulation results to analyze effectiveness of the proposed method.
Lecture Notes in Computer Science, 2023
Recent rapid developments in reinforcement learning algorithms have been giving us novel possibil... more Recent rapid developments in reinforcement learning algorithms have been giving us novel possibilities in many fields. However, due to their exploring property, we have to take the risk into consideration when we apply those algorithms to safety-critical problems especially in a real environment. In this study, we deal with a safe exploration problem in reinforcement learning under the existence of disturbance. We define the safety during learning as satisfaction of the constraint conditions explicitly defined in terms of the state and propose a safe exploration method that uses partial prior knowledge of a controlled object and disturbance. The proposed method assures the satisfaction of the explicit state constraints with a pre-specified probability even if the controlled object is exposed to a stochastic disturbance following a normal distribution. As theoretical results, we introduce sufficient conditions to construct conservative inputs not containing an exploring aspect used in the proposed method and prove that the safety in the above explained sense is guaranteed with the proposed method. Furthermore, we illustrate the validity and effectiveness of the proposed method through numerical simulations of an inverted pendulum and a four-bar parallel link robot manipulator.
2018 Annual American Control Conference (ACC)
This paper addresses optimal power demand management in the electricity market. First, we model t... more This paper addresses optimal power demand management in the electricity market. First, we model the behavior of players, consumers, aggregators, and the market. Each consumer entity acts to maximize its own profit. The aggregator decides how much individual consumer power demand should be reduced if total power demand exceeds power generation constraints. We propose a method for an aggregator to make this decision using mechanism design and matching theory. Finally, we show that an algorithm can manage power demand and improve consumers' profits using simulation results. "Smart grids" are attracting attention as a means of controlling power flow in power networks on the basis of both supply and demand for effective utilization of energy. Smart grids are intended to shift peaks in response to increased power demand, prevent resulting power failures, and counter environmental problems such as global warming and issues with nuclear energy. In Japan, transmission and distribution networks have already been reorganized to a certain degree in order to provide power on a stable basis. Thus, it is expected that smart grids will be constructed in Japan to introduce renewable energy as a measure against power failures. However, the main forms of renewable energy generation-solar and wind power-depend upon the weather, which makes regulating power generation difficult. When actual power generation deviates significantly from predictions, the supply and demand balance is disrupted, and may threaten power system safety. Lower-than-predicted power generation in particular may result in greater required power saving by consumers. Various methods have been studied to respond to these issues. The purpose of this paper is to address demand response, and resolve instances of insufficient supply through power interchange with other areas, and reduce consumer power consumption. In addition, Japan's power market was completely liberalized in 2016, so consumers are now able to choose the suppliers from which they purchase power. This means it is important to imagine that power is being purchased from multiple suppliers, and that suppliers are being chosen on the basis of which is the most economical in terms of demand. An additional purpose of this paper is to address the distribution of consumer power purchases, and how consumers can obtain the maximum profits.
Transactions of the Society of Instrument and Control Engineers
In this paper, we propose a novel Smart Parking System which determines optimal parking lot alloc... more 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.
arXiv (Cornell University), Sep 30, 2022
Recent rapid developments in reinforcement learning algorithms have been giving us novel possibil... more Recent rapid developments in reinforcement learning algorithms have been giving us novel possibilities in many fields. However, due to their exploring property, we have to take the risk into consideration when we apply those algorithms to safety-critical problems especially in a real environment. In this study, we deal with a safe exploration problem in reinforcement learning under the existence of disturbance. We define the safety during learning as satisfaction of the constraint conditions explicitly defined in terms of the state and propose a safe exploration method that uses partial prior knowledge of a controlled object and disturbance. The proposed method assures the satisfaction of the explicit state constraints with a pre-specified probability even if the controlled object is exposed to a stochastic disturbance following a normal distribution. As theoretical results, we introduce sufficient conditions to construct conservative inputs not containing an exploring aspect used in the proposed method and prove that the safety in the above explained sense is guaranteed with the proposed method. Furthermore, we illustrate the validity and effectiveness of the proposed method through numerical simulations of an inverted pendulum and a four-bar parallel link robot manipulator.
Transactions of the Society of Instrument and Control Engineers, 2020
This paper deals with photovoltaic (PV) power prediction and building energy management system (B... more This paper deals with photovoltaic (PV) power prediction and building energy management system (BEMS) in multiple buildings. First, we consider PV power prediction. We predict PV power by using k-means method and SVR. However, there is an error between prediction and actual generation. In order to solve this issue, we estimate prediction error in advance by markov process and revise the prediction. And, by applying copula to calculated point prediction, calculate interval prediction. Second, we consider 2 level BEMS. At first level, in each building, power consumption is determined considering comfort. At second level, in order to reduce total cost in all buildings, battery scheduling is calculated with robustness by applying scenario robust theory. And, at the end of each section, simulation results show the effectiveness of proposed prediction method and energy management method.
This paper deals with state estimation of H∞ filter and switching of network considering state es... more This paper deals with state estimation of H∞ filter and switching of network considering state estimation error and communication energy of sensor network. The proposed algorithm with H∞ filter acheive network topology with munimum energy and desired estimation accuracy. experimental results show effectiveness of proposed method.
IET Smart Grid, 2020
In this study, networks of interconnected heterogeneous micro-grids are studied. The transient dy... more 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.
2019 IEEE Data Science Workshop (DSW), 2019
For a population of electric vehicles (EVs) we design a data-driven mean-field game and provide a... more For a population of electric vehicles (EVs) we design a data-driven mean-field game and provide analysis of approximated mean-field equilibrium points based on a receding horizon approach. The model involves stochastic disturbances on the data that drive the game. Some numerical studies illustrate the efficacy of the proposed strategies.
In this paper, the problem of determining the size of battery storage used in grid-connected phot... more In this paper, the problem of determining the size of battery storage used in grid-connected photovoltaic(PV) systems is discussed. In this problem, our goal is to find optimal capacity and charge/discharge planning for Li-ion batterys to minimize the power purchase cost. We propose a novel charge/discharge planning method based on optimization technique considering Li-ion battery characteristics to expand battery life. Finally, the effectiveness of the proposed method is shown via simulations.
2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2018
This paper deals with merging control of automated vehicles using distributed model predictive co... more This paper deals with merging control of automated vehicles using distributed model predictive control. We consider a road model which has two main lanes. In the distributed control algorithm, vehicles repeat sharing the planned future trajectory with other vehicles traveling in the vicinity of each vehicle by using communication and replanning its own trajectory considering the future trajectory of other vehicles. Moreover, in order to further improve the stability of model predictive control, terminal constraints are set and feasible conditions for optimization problems under the terminal conditions are derived. At the last part of this paper, we confirm the effectiveness of proposed methods through simulations.
SICE Journal of Control, Measurement, and System Integration, 2020
This paper presents the optimal motion planning problem for connected and automated vehicles (CAV... more This paper presents the optimal motion planning problem for connected and automated vehicles (CAVs) to cross a conflict area at an intersection with state and control constraints. First, we formulate the scheduled merging (or crossing) time for all CAVs as a mixed integer linear programming (MILP) problem where the merging time is solved frequently. Second, we formulate the optimal motion planning problem so that the CAVs can achieve their scheduled merging time as well as minimizing the energy consumption. Since we solve the motion planning problem analytically, not all the solutions are feasible to comply with the frequently updated merging time. To solve this problem, we propose a feasibility enforcement period (FEP). Then, we validate the proposed solution through simulation, and the results show that even the merging time is frequently updated, the CAVs can still achieve the merging time with a minimal deviation. Besides, our proposed framework also shows a significant improvement in terms of travel time as compared to the conventional one.
SICE Journal of Control, Measurement, and System Integration, 2019
This paper addresses the crossing order problem for connected and automated vehicles at an inters... more This paper addresses the crossing order problem for connected and automated vehicles at an intersection where the problem can lead to higher traffic congestion, especially in high traffic density. First, we formulated the problem with mixed integer linear programming where the solution yields optimal crossing time for each vehicle to cross the intersection. Then, we present an optimization framework to drive each vehicle towards the assigned crossing time while conserving the fuel consumption. Finally, we simulate the intersection scenario with the proposed solution, where it is shown that both congestion and fuel consumption can be reduced significantly.
Transactions of the Society of Instrument and Control Engineers, 2018
This paper deals with merging control of automated vehicles using distributed model predictive co... more This paper deals with merging control of automated vehicles using distributed model predictive control. Firstly, we consider a road model which has two main lanes. In the distributed control algorithm, vehicles repeat sharing the planned future trajectory with other vehicles traveling in the vicinity of each vehicle by using communication and re-planning its own trajectory considering the future trajectory of other vehicles. Moreover, in order to further improve the stability of model predictive control, terminal constraints are set and feasible conditions for optimization problems under the terminal conditions are derived. At the last part of this paper, we discuss the result of numerical simulations using distributed merging control algorithm and mention the effectiveness of proposed methods and future works.
Transactions of the Society of Instrument and Control Engineers, 2018
This paper deals with a power demand-supply management based on negawatt trading, and the purpose... more This paper deals with a power demand-supply management based on negawatt trading, and the purpose of this research is to keep demand supply balance and to minimize the social cost of negawatt trading, balancing generator, and power flow. In this research, consumer and Independent System Operator (ISO) participate in the electricity market, and each consumer acts based on Regret Matching which is one of the learning algorithms. Furthermore, as the incentive design of negawatt trading, we consider strategy-proofness and individual rationality using VCG mechanism design. Then, we propose a novel negawatt trading algorithm based on Regret Matching and VCG mechanism design. Finally, simulation results show the effectiveness of the proposed algorithm.
Transactions of the Society of Instrument and Control Engineers, 2018
In this paper, load frequency control problem for power system is discussed. The control is condu... more In this paper, load frequency control problem for power system is discussed. The control is conducted to retain power demand supply balance by controlling output of generators in power network. However, it becomes harder to retain the balance because of large volume injection of renewable energy whose output is uncertain. To resolve the problem, some approaches are considered in this research field. One is to use dispersion type power sources like battery in addition to conventional generators like thermal power generator and hydroelectric generator. Another is to apply new control theories and methods. The other is the load frequency control considering demand response by using a controllable load on the consumer side. Especially among them, in this paper, power system which holds large volume wind turbine generator, turbine generator and battery is focused on and new control method is proposed. Concretely, load frequency control based moving horizon estimation and robust model predictive control is proposed in order to satisfy the constraints of state and control input.
IEEJ Transactions on Electronics, Information and Systems, 2019
In this paper, we propose a novel control method which combine collision avoidance method and RIS... more In this paper, we propose a novel control method which combine collision avoidance method and RISE(Robust Integral of the Sign of Error) for multiple Quad-rotor formation control methods for cooperative control, and confirm effectiveness of this method by experiment using actual Quad-rotor. First, this work describes a method to suppress nonlinear disturbance using RISE which is a type of sliding mode control. In addition, collision avoidance method and the conditions to achieve accurate formation are explained. Finally, the effectiveness of proposed method is confirmed functioning correctly, by implemented an algorithm in the actual Quad-rotor.
Transactions of the Society of Instrument and Control Engineers, 2019
In this paper, we propose a control method which combine collision avoidance method and RISE (Rob... more In this paper, we propose a control method which combine collision avoidance method and RISE (Robust Integral of the Sign of Error) for multiple Quad-rotor formation control methods, and confirm effectiveness of this method that is resistant to disturbance by lowering the risk of collision. First, we modeled quad-rotor as a linear system. Next, we described a method to suppress nonlinear disturbance using RISE which is a type of sliding mode control. In addition, we introduced collision avoidance method, and derived the conditions to achieve accurate formation by using Lyapunov stability theory. Finally, we implemented an algorithm in the simulation, and confirmed that the proposed method is functioning correctly.
IFAC-PapersOnLine, 2018
The purpose of this paper is to achieve a cut in peak electricity demand and lower electricity co... more The purpose of this paper is to achieve a cut in peak electricity demand and lower electricity costs through the optimal management of a heating ventilation and air conditioning (HVAC) system. In addition, robust solar radiation prediction is required for optimal HVAC management. First, solar radiation prediction is applied using a clustering technique based on the k-means method, classifying all data on similar types of solar radiation. Second, an H ∞ filter, which is a robust prediction method for outliers, is applied. Next, an optimal HVAC management system is considered for operating the air conditioning, such as the cooling and heating of each room. Model predictive control (MPC), which is used to predict and control the future changes in the temperature of the room and the electrical charge from solar radiation, is applied. Finally, we confirmed the validity of this research through numerical simulations.
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Papers by Toru Namerikawa