Published papers

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.

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.

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.

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.

This paper deals with the Simultaneous Localization and Mapping problem via H1 filter considering finite escape time. The estimation via H1 filter occurs finite escape time depending on the value of the parameter γ and then the estimation fails or deteriorates. In order to avoid it, we propose a novel algorithm of the update equation of the filter gain. The convergence of the error covariance matrices are proven. In simulation and experimental results, the avoidance of the finite escape time and the correctness of derived theorems for the convergence are confirmed and then we can show robot’s state and environment information can be estimated.

This paper deals with game theoretic real-time pricing method based on dual decomposition and its application to load frequency control of power networks. The proposed pricing method in this study aims to solve the　constrained optimization problem consist of each player’s utility and social welfare under selfish players. Selfish　player’s decision is a Nash equilibrium solution considering their own cost functions. We show this method can　lead their own decision to social welfare maximization. Finally we show the effectiveness of the proposed　methodology for load frequency control by several simulation results.

本稿ではまずセンサの観測値にバイアスがかかるような故障に関して観測誤差共分散を用いた故障検出を行う．そしてこの結果と文献の観測値欠落を考慮したを組み合わせて故障の発生に対して状態推定精度を高感度化することにより故障信号の付加により信頼性の低下した観測値の状態推定結果への反映を抑制した推定手法を提案する．次に現時刻の観測データを含む状態推定値の欠落に対し観測値の推定値を用いた補償を行うことで推定精度を向上させる手法を提案し最後にこれらの提案制御則の有効性をシミュレーションにより検証する．次章以降ではまずはじめに問題設定としてセンサノードと制御対象であるプラントのモデル本稿で扱う種類の耐故障問題に関しての定義について述べる．次に設定した評価関数の特性について述べこの性質を利用した近傍比較戦略を提示する．最後に数値シミュレーションと制御実験により提案手法の有効性を検証した結果を示す．

This paper deals with modeling, structured uncertainties, mu-analysis and synthesis of a magnetic suspension system. First we derive a nominal model of the plant and consider its structured uncertainties e.g., linearization error, parametric uncertainties, and neglected dynamics. Then we set the interconnection structure which includes the above structurally represented uncertainties. Next we design a robust mu controller which achieves robust performance condition using the structured singular value mu. Finally we evaluate the proposed interconnection structure and verify robustness and performance of the designed mu controller by experiments.

In this paper, we present a robust control for a flexible-joint robot manipulator using linear parameter varying representation. The robot manipulator dynamics can be brought to a quasi linear parameter varying (LPV) form by a state transformation. An LPV system is defined as a linear system whose dynamics depend on an exogenous variable which can be measured upon system operation. In this case, the scheduling variables are the joint angles q. which are state variables. Using a quasi-LPV form, we design a robust controller by mu-synthesis to achieve robust performance specification.

This paper deals with a robust control scheme for a flexible-joint robot manipulator using a linear parameter varying representation. We show this system can be brought to a quasi linear parameter varying (LPV) form by a state transformation. Using this form, we design a controller by mu-synthesis to achieve robust performance.

This paper deals with modeling, uncertainty description and robustness analysis of a magnetic suspension system. First we derive a nominal model of the plant and consider its uncertainties e.g., linearization error, parametric uncertainties, and neglected dynamics. Then we set the interconnection structure which includes the above structurally represented uncertainties. Next the analysis of robust stability/performance for the obtained interconnection structure with three-types controllers by mixed structured singular value (mixed mu). Finally we evaluate the robustness of the proposed models and analytic results by experiments.

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 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 propose the regression model for wind speed and wind power, and the unknown parameters are estimated via constrained kalman filter. Moreover, in a procedure of estimation of the unknown parameters, reduction and the convergence of them are also guaranteed. Finally, the advantages of the proposed method over the conventional method are shown through actual prediction evaluations.