Details of a Researcher - Namerikawa, Toru

Presentations -

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RISE-based robust formation control for multi-UAV system

Komagine Yu, Toyota Ryo, Kotani Kento, Namerikawa Toru

2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE),

2017.11

Oral presentation (general)

This paper deals with a robust formation control methodology for the Multi-UAV system with uncertain exogenous disturbance. The fourth-order UAV model with disturbance and the disturbance estimate system is introduced. In order to achieve the rigid formation fight, graph theory and consensus algorithm are utilized and the state of the UAVs converges to desired value by using Leader-Follower structure. The proposed control law includes the Robust Integral of the Sign of error (RISE) for estimation of the disturbance and also involves collision avoidance property based on potential method. The stability and convergent properties are proven based on Lyapunov theory. Finally, several simulation results show the effectiveness of the proposed method compared with a conventional sliding mode control.

Formation control of multi-agent system considering obstacle avoidance

Toyota Ryo, Namerikawa Toru

2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE),

2017.11

Oral presentation (general)

This paper deals with distributed and cooperative control algorithm to make each agents to form a formation for a second-order system. However, when forming a formation with a multi-agent system, there is a possibility that the agents collide with each other or collide with obstacles other than the agent. Also, if the agents avoid other agents and obstacles, the distance between agents may be temporarily too far apart. In order to solve these problems, this paper proposes a control algorithm which consists of Leader-Follower structure, consensus algorithm and artificial force based on artificial potential field. For the control algorithm to make agents achieve formation in a decentralized cooperative way, we derive the condition concerning the control gain to ensure stability. In addition, by comparing the amount of energy, we design conditions that ensure collision avoidance between agents, collision avoidance with obstacles, and distance between agents, and also design potential functions that satisfy the conditions. The validity of the control algorithm proposed in this paper is verified by numerical simulations.

Collision Avoidance between Multi-UAV-Systems considering Formation Control using MPC

Ille Marc, Namerikawa Toru

2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM),

2017.08

Oral presentation (general)

This paper deals with the scenario of two multi- UAV systems (so-called teams), each flying from a starting point to a target point. The teams meet on their ways and have to avoid collisions in the horizontal plane. Both teams work independent of each other but use the same formationcontrol and obstacle-collision-avoidance algorithm. The leaders measure obstacles' positions, use a Kalman Filter to estimate their movement and predict their future positions. With the information about the other agents' positions each agent calculates its reference trajectory. The leader also computes a trajectory to guide the team towards the target point. Distributed MPC is used for each agent to track its reference trajectory. If there is a risk of colliding with an obstacle, the MPC cost function is extended by a penalty term to ensure obstacle collision avoidance. The stability of formation control is proved in this paper. The capability of two teams avoiding collisions is shown in a simulation.

RISE-based cooperative control of uncertain multi-agent system

Tachibana Yoshihiro, Namerikawa Toru

2017 American Control Conference (ACC),

2017.06

This paper proposes a RISE-based cooperative control of uncertain multi-agent system with exogenous disturbances. First, we introduce the second order model with disturbance for agent. The network topology among agents is undirected and connected, and information of reference is allowed to be available to at least one agent. Second, we propose the control law consists of graph theory, consensus algorithm and RISE. Graph theory and consensus algorithm are utilized to converge the states of agents to reference value, and RISE is utilized to suppress the disturbance. Then, we show the proposed control law guarantees the agents achieve synchronization, and derive the condition to achieve the control objective. Finally, simulation results show the effectiveness of the proposed control law.

Detection of replay attack on smart grid with code signal and bargaining game

Irita Takashi, Namerikawa Toru

2017 American Control Conference (ACC),

2017.06

Oral presentation (general)

Ensuring cyber security of smart grid based on supervisory control and data acquisition using information and communications technology has been becoming a major challenge. Especially, a replay attack is a dangerous cyber attack affecting integrity and authorization. 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.

Transient dynamics of heterogeneous micro grids using second order consensus

Mendoza Fernando Genis, Bauso Dario, Namerikawa Toru

2017 International Conference on Wireless Networks and Mobile Communications (WINCOM),

2017.01

Oral presentation (invited, special)

This paper deals with a network of interconnected micro grids. The transient dynamics is modelled as an averaging process involving dynamic agents in a network. An analysis of the convergence of the consensus dynamics is provided using a network model based approach and by exploiting the properties of the corresponding graph-Laplacian matrix. Furthermore an investigation of the transient dynamics is carried out for different damping and inertial parameters and under different timevarying topologies. Finally a simulation is performed based on a model calibrated on an existing network in the UK under parameter uncertainties.

Optimal Power Demand Management among Consumers with Aggregator considering State and Control Constraints

Yoshihiro Okawa and NAMERIKAWA Toru

2016 IEEE 55th Conference on Decision and Control (CDC) ARIA Resort & Casino (Las Vegas, USA) ,

2016.12

Oral presentation (general)

This paper presents a novel optimal power demandmanagementmethodforpowerconsumerswithanaggregator considering state and control constraints. The aggregator is an organization who manages some consumers to achieve demand response efﬁciently. This paper proposes a power demand adjustment method for the aggregator to allocate power reduction among consumers in a distributed manner. Speciﬁcally, this method simultaneously derives the optimal power reduction of each consumer using a gradient method and determines the control inputs by solving a quadratic programming problem with state and input constraint conditions. This paper also shows the convergence of the proposed algorithm, and ﬁnally, numerical simulation results illustrate the effectiveness of the proposed method.

A Comparative Study of Extended Kalman Filter and H∞ Filtering For State Estimation of Stewart Platform Manipulator

Shady A. Maged, A. A. Abouelsoud, Ahmed M. R. Fath El Bab and NAMERIKAWA Toru

Proceedings of the SICE Annual Conference 2016 (つくば市) ,

2016.09

Oral presentation (general)

This paper presents the estimation of both position and velocity of Stewart Manipulator by means of limbs potentiometer measurements and MEMS inertial sensors. The estimation used the Extended Kalman Filter (EKF) and H∞ optimal filtering technique based on the combination of these sensors. The two types of filters are used as nonlinear state estimators to the Stewart platform which is modeled as a stochastic differential equations due to measurement noise in case of EKF and as a continuous time system model in case of H∞ filtering technique. The results of the both filters are compared with each other on the Stewart platform DELTALAB EX800 using MATLAB SimMechanics toolbox. The simulation results show that Kalman filters are not the best choice for parallel manipulator state estimation as they bear from the hypothesis of statistical noise with zero mean as well as known noise covariance, which may reduce its performance. For these reasons, H∞ filter may be the alternative of Kalman filter.

Optimal pricing algorithm to suppress voltage rise caused by reverse load ﬂow in power distribution grid

Kentaro Nagami and NAMERIKAWA Toru

Proceedings of the SICE Annual Conference 2016 (つくば市) ,

2016.09

Oral presentation (general)

On the Fault Tolerant Control of a Quadrotor Manipulation System via MPC and DOb Approaches

Ahmed Khalifa, Mohamed Fanni and NAMERIKAWA Toru

Proceedings of the SICE Annual Conference 2016,

2016.09

Oral presentation (general)

Recently, the Aerial Manipulation System becomes very attractive for a wide range of applications due to its unique features. However, control of such system is quite challenging. One of the critical challenge is that this system is verysusceptibletoactuators’faults. Inthispaper,aPassiveFaultTolerantControlSystemisproposedtoaddressthisissue withrobustandoptimalperformance. TherobustnessisachievedusingalinearDisturbanceObserver(DOb)loop. Based on the linearization capability of DOb, a standard Model Predictive Control (MPC) is then used and the resulting control scheme is characterized by both a low computational load and optimal actuators’ efforts with respect to conventional nonlinear robust solutions. This controller is tested to achieve the tracking of a point-to-point task space references under the effect of actuators’ faults, picking/releasing a payload, changing the operating region, and measurement noise. Efﬁcacy of the proposed technique is veriﬁed via numerical simulations.

SLAM for a Small UAV with Compensation for Unordinary Observations and Convergence Analysis

Takumi Shinohara and NAMERIKAWA Toru

Proceedings of the SICE Annual Conference 2016,

2016.09

Oral presentation (general)

This paper deals with the Simultaneous Localization and Mapping (SLAM) problem for a small Unmanned Aerial Vehicle (UAV) via extended Kalman Filter (EKF) with compensations for unordinary observations. In the SLAM problem, a robot sometimes loses its proper observations then the estimation accuracy deteriorates. In this paper, to remove the effects of unordinary observations, we propose a novel SLAM method considering unordinary observation based on Mahalanobis distance. The proposed method detects the unordinary observations by comparing the observation values with its estimation and determines the weight of these observations. The convergence of the state error covariance matrix is proven. In experimental validation, we show that the UAV state and environment information can be estimated with the proposed method.

Optimal Trafﬁc Signal Control for Alleviation of Congestion based on Trafﬁc Density Prediction by Model Predictive Control

Hiroaki Nakanishi and NAMERIKAWA Toru

Proceedings of the SICE Annual Conference 2016 (つくば市) ,

2016.09

Oral presentation (general)

The purpose of this paper is to propose an optimal trafﬁc signal control in accordance with trafﬁc density to change every moment in trafﬁc network. We focus on calculating optimal signaling split based on trafﬁc volume prediction by model predictive control. Therefore, we aim the achievement of alleviation of congestion in trafﬁc network considering actual trafﬁc situation. Finally the achievement of the purpose is evaluated by controlling of trafﬁc signal in numerical simulations and the relationship between green time and trafﬁc density is examined.

Flocking Algorithm for Multiple Nonholonomic Cars

Yasuhiro Hayashi1 and NAMERIKAWA Toru

Proceedings of the SICE Annual Conference 2016,

2016.09

Oral presentation (general)

In this paper, a ﬂocking control algorithm for multiple nonholonomic cars is proposed. First, it is shown that the nonholonomic car is linearized by using a virtual vehicle. Second, we deﬁne a metric and topological neighborhood set in order to decide which cars to be next to the other car. Control objectives consist of three rules in boids model as separation, alignment, and cohesion, which is a well-known framework of emerging ﬂock, advocated by Reynolds in 1986. Using the neighborhood set, we show the formation of ﬂocking corresponds to the model. These cars are supposed tobeonastraighthighway,whichenablesustosetanassumptionthateachcarheadstothesamedirectionandreachesthe same velocity eventually. The input for a car consists of the artiﬁcial potential method and LaSalle’s invariance principle is utilized to prove the convergence of the entire vehicle system. Finally, the effectiveness of the presented method is examined through simulation.

Robust-Formation Control of Multi-Autonomous Underwater Vehicles based on Consensus Algorithm

Vina Putranti, Zool H. Ismail and NAMERIKAWA Toru

2016 IEEE Conference on Control Applications (CCA) Part of 2016 IEEE Multi-Conference on Systems and Control (Buenos Aires, Argentina) ,

2016.09

Oral presentation (general)

SoC regulator and DOB-based Load Frequency Control of a Microgrid by Coordination of Diesel Generator and Battery Storage

Takuto Hiranaka, Hyungbo Shim, and NAMERIKAWA Toru

2016 IEEE Conference on Control Applications (CCA) Part of 2016 IEEE Multi-Conference on Systems and Control (Buenos Aires, Argentina) ,

2016.09

Oral presentation (general)

In this paper, the load-frequency control problem of microgrid is discussed. The control is applied to maintain a balance between electric-power demand and supply by controlling the outputs of generators in power systems. However, because of the large-scale introduction of energy from renewable-energy sources, it has become more difﬁcult to maintain this balance. To solve this problem, we consider introducing batteries to microgrid. Therefore, we focus on a microgrid that comprises wind-turbine generators, loads, diesel generators, and batteries. First, we design a generalized plant including the diesel generators and batteries. Then, we apply disturbance observer to decide a reference input to diesel generators and batteries. And, we split the reference input into that for diesel generators and that for batteries considering the differences in the response speeds by applying low-pass ﬁlter. Furthermore, we apply SoC regulator for the state of charge of batteries reaching maximum capacity or minimum capacity. Finally, we perform numerical simulations to verify that the control method can suppress the frequency deviations and deviations in the residual capacity of the battery.

Hybrid Acceleration/Velocity-based Disturbance Observer for a Quadrotor Manipulation System

Ahmed Khalifa, Mohamed Fanni and NAMERIKAWA Toru

2016 IEEE Conference on Control Applications (CCA) Part of 2016 IEEE Multi-Conference on Systems and Control (Buenos Aires, Argentina) ,

2016.09

Oral presentation (general)

Aerial manipulation systems become very attractive for a wide range of applications due to their unique features. However, control of such system is quite challenging due to its high nonlinearities, couplings, and external disturbances. In this paper, a Disturbance Observer (DOb)-based linearization of a quadrotor manipulation system is utilized. The DOb estimates the disturbances and nonlinearities, then compensates them such that one can treat the control problem based on a simple linear control algorithm. However, the current developed DOb schemes in the literature are based on the precise measurement of the acceleration or the estimation of the velocity. Unlike, these methods, we propose a modiﬁed DOb, which is based on both the measured linear accelerations and angular velocities that can be obtained directly from the onboard Inertial Measurement Unit (IMU) and encoders. With this technique, the estimation of nonlinearities and disturbances are carried out without the need of estimation acceleration or velocity, and it is model free. The Effectiveness of the proposed technique is veriﬁed via numerical simulations.

Hierarchical and Cooperative Model Predictive Control for Load Frequency of Power Network

ShunTakamura andNAMERIKAWA Toru

Proceedings of the 35th Chinese Control Conference,

2016.07

Oral presentation (general)

In this paper, frequency control problem of a power network is discussed. The control is conducted to retain power demandsupplybalancebycontrollingoutputofgeneratorsinpowernetwork. However,itisgettinghardertoretainthebalance because of large amount of renewable energy injection. This paper proposes more economic and ef¿cient frequency control method based on hierarchical model predictive control. At ¿rst, we describe model of the power network. Then, the frequency control based on hierarchical and cooperative model predictive control is proposed. The proposed control method consists of economic dispatch and load frequency control. In numerical simulation, we show the effectiveness of the proposed method comparedwiththeconventionalloadfrequencycontrolmethodintermsofsuppressionoffrequencyvariationandfuelcost.

MPC and DOb-based Robust Optimal Control of a New Quadrotor Manipulation System

Ahmed Khalifa, Mohamed Fanni and NAMERIKAWA Toru

2016 European Control Conference,

2016.06

Oral presentation (general)

This paper introduces motion control scheme of a new aerial manipulation system that consists of 2-link manipulator attached to the bottom of a quadrotor. This new system presents a solution for the limitations found in the current quadrotor manipulation systems. It is very attractive for a wide range of applications due to their unique features. However, control of such system is quite challenging because it is naturally unstable, has strong nonlinearities and couplings, has fast dynamics, is very susceptible to parameters variations due to carrying a payload besides the external disturbances like wind, and has actuator limitations. A robust optimal linear control scheme is proposed to address these issues. The proposed control scheme is based on a hybrid linear Model Predictive Control (MPC) and linear Disturbance Observer (DOb) techniques.

Distributed Power Supply-demand Management Based on Negawatt Trading with Energy Storage System

Yoshihiro Okawa NAMERIKAWA Toru

2016 European Control Conference,

2016.06

Oral presentation (general)

—This paper presents a distributed power supplydemand management method based on negawatt trading includingchargeordischargepowerfromenergystoragesystems. In the negawatt trading, power consumers reduce their own power demand and receive monetary reward from the market operator. In order to derive appropriate electricity incentive pricesforconsumersandtouseenergystoragesystemsinpower grids efﬁciently, we deal with a power adjustment problem using some future power supply information in this paper. We then show a novel market algorithm to solve this problem in a distributed manner through market trading among the market operator and consumers. Finally, we verify the effectiveness of our proposed method with numerical simulation results.

Load frequency control of a microgrid based on H∞ control considering response speed of generators

Kenji Masui and Toru NAMERIKAWA

Proc. of IEEE Conference on Decision and Control,

2015.12

Oral presentation (general)

In this paper, we discuss the load-frequency control problem of microgrids.
First, we use dispersion-type power sources such as batteries, and secondly, we apply new control theories. Therefore, we focus on a microgrid that comprises a wind-turbine generator, a diesel generator, and a battery, and we propose a technique based on static H∞ control. First, we design a generalized plant considering the differences in the response speeds of diesel generators and batteries. Then, we apply static H∞ control to the generalized plant. Moreover, we combine a linear matrix inequality (LMI) condition with static H∞ control to avoid control gains that will result in control inputs that are too large. We perform numerical simulations to verify that the controller can suppress the frequency deviations and deviations in the residual capacity of the battery. Furthermore, we show that the approach can be employed to design controllers with lower dimensions, and to avoid undesirable control gains. Finally, we perform experiments using a generator and a variable resistance to confirm the effectiveness of the controller.

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