Details of a Researcher - Ohmori, Hiromitsu

Papers - Ohmori, Hiromitsu

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Extremum Seeking Based on Approximated Sign of Gradient of Unknown Plant Maps

Yamanaka O., Onishi Y., Hiraoka Y., Hidaka K., Ohmori H.

2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020 (2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020) 249 - 254 2020.09

This paper presents a novel perturbation-based extremum seeking (ES) based on the smooth approximation of the sign of the gradient of unknown plant maps, which will improve the stability and the control performance of ES. The stability and the convergence speed of conventional sinusoidally perturbed gradient-based ES are very sensitive to the curvature of an unknown plant map, which has motivated the development of improved ES schemes that are less sensitive to the curvature such as Newton-like ES schemes. In this paper, an alternative ES scheme is proposed by estimating the sign of the gradient instead of the gradient itself. The ES scheme not only frees us from taking care of the curvature of the unknown map but also is able to minimize the increase of implementation complexity by just incorporating the signum function for the conventional ES scheme. Moreover, the signum function is replaced by its smooth approximation such as the softsign or a sigmoid function in order not only to suppress chattering phenomena but also to be able to adjust the behavior in the vicinity of an extremum point. It is also shown that the local-stability of the proposed ES scheme can be proved under some mild assumptions for the approximation function. The effectiveness of the proposed ES is demonstrated by some simulation examples for a simple process model and for a complex nonlinear biological wastewater treatment process model.

Model predictive control for concentrating solar power plants with thermal energy storage system

Terunuma R., Ohmori H.

This study proposes a model predictive controller for concentrating solar power (CSP) plants. Few studies have considered a thermal energy storage system and a power system. The proposed model predictive controller maintains the heat transfer fluid temperature by manipulating its mass flow rate and stabilizes the power frequency by balancing power supply and demand. In the case of the direct normal irradiance is low, the thermal energy storage system makes up for the shortage of thermal. The simulation using actual solar direct normal irradiance data and electricity demand data shows the proposed controller contributes to stable operation of CSP plants.

Extremum Seeking Control for Wastewater Treatment Plant with Prioritized Output Constraints

Onishi Y., Yamanaka O., Nishimura Y., Kato K., Hidaka K., Fukuda N., Ohmori H.

This paper is concerned with the applicability of extremum seeking (ES) control for wastewater treatment plants (WWTPs) under several practical constraints such as effluent regulations and/or operational constraints. Considering such constraints to optimize a trade-off between effluent improvement and operational cost reduction is important in real WWTP operation. To meet such practical requirements, this paper proposes a novel ES scheme incorporating multiple output constraints where the priority of each constraint is also considered. Such priority becomes important when one or more of the constraints cannot be satisfied, which will not be the exception in control problems of real WWTP due in part to the considerably large inflow load variation. To make ES be effective even in such situation, the paper proposes a prioritized output constraints ES scheme incorporating switching functions to change the performance index for minimization depending on the active constraints. It is suggested that such switching mechanism is preferably combined with the gradient-sign-based ES that was also proposed by the authors to mitigate the sudden change in the curvature of the performance index caused by the switching functions. Some numerical simulations of the proposed ES with a simple model are performed to illustrate the principle of the proposed idea at first, and then the effectiveness of the proposed ES to WWTPs is demonstrated by using a complex nonlinear biological model.

Subspace-Based Near-Field Source Localization in Unknown Spatially Nonuniform Noise Environment

Zuo W., Xin J., Zheng N., Ohmori H., Sano A.

IEEE Transactions on Signal Processing (IEEE Transactions on Signal Processing) 68 4713 - 4726 2020

ISSN 1053587X

In this paper, we investigate the problem of estimating the directions-of-arrival (DOAs) and ranges of multiple narrowband near-field sources in unknown spatially nonuniform noise (spatially inhomogeneous temporary white noise) environment, which is usually encountered in many practical applications of sensor array processing. A new subspace-based localization of near-field sources (SLONS) is proposed by exploiting the advantages of a symmetric uniform linear sensor array and using Toeplitzation of the array correlations. Firstly three Toeplitz correlation matrices are constructed by using the anti-diagonal elements of the array covariance matrix, where the nonuniform variances of additive noises are reduced to a uniform one, and then the location parameters (i.e., the DOAs and ranges) of near-field sources can be estimated by using the MUSIC-like method, while a new pair-matching scheme is developed to associate the estimated DOAs and ranges. Additionally, an alternating iterative scheme is considered to improve the estimation accuracy of the location parameters by utilizing the oblique projection operator, where the 'saturation behavior' caused by finite number of snapshots is overcome effectively. Furthermore, the closed-form stochastic Cramér-Rao lower bound (CRB) is also derived explicitly for the near-field sources in the additive unknown nonuniform noises. Finally, the effectiveness of the proposed method and the theoretical analysis are substantiated through numerical examples.

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Diesel Engine Combustion Control with Onboard Calibration by Using Feedback Error Learning

Eguchi M., Fukuda N., Ohmori H., Takahashi M., Yamasaki Y., Kaneko S.

SAE Technical Papers (SAE Technical Papers) ( December ) 2019.12

© 2019 SAE Japan and SAE International. In this paper, we propose an onboard calibration method based on the feedback error learning (FEL). This controller is 2 degree of freedom controller. We use a cerebellar model articulation controller (CMAC) as the feedforward controller. By using this, fast learning will be possible. Due to the online learning of this controller, it becomes possible to correspond to changes in the environment such as aging. In this paper, we constructed FEL considering the premixed diesel combustion with dual peak heat release rate under transient operation. To confirm the effectiveness of this control system, experimental results will be shown.

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Solar parabolic trough thermal energy output forecasting based on K-Nearest Neighbors approach

Jafferi Jamaludin、Hiromitsu Ohmori

Earth and Environmental Science (ESS) (Open access IOP Conference Series) 342 ( 1 ) 2019.10

Research paper (scientific journal), Accepted

Diesel Engine Combustion Control with Onboard Calibration by using the Feedback Error Learning

Makoto Eguchi, Naoki Fukuda＊, and Hiromitsu Ohmori　(Keio University), Motoki Takahashi, Yudai Yamasaki and Shigehiko Kaneko (University of Tokyo)

2019 JSAE/SAE Powertrains, Fuels and Lubricants (P, F&L)　International Meeting, JSAE Paper Number: 20199037, SAE 2019-01-2318 (JSAE Paper) 2019.08

Research paper (international conference proceedings), Accepted

Impact of Query Information on Electricity demand forecasting based on K nearest neighbor Model

Jafferi Jamaludin(Univ. Malaya) and Hiromitsu Ohmori

International Conference on Renewable Energy and Conservation (ICREC) 2019 (Hiroshima, Japan) 2019.06

Research paper (international conference proceedings), Accepted

Evaluation of model based control for multi-stage heat release of advanced diesel combustion

Yudai Yamasaki, Motoki Takahashi, Shigehiko Kaneko, Seiya Fujii, Ikuro Mizumoto, Tomofumi Hayashi, Mitsuo Hirata, Makoto Eguchi, Hiromitsu Ohmori

Symposium for Combustion Control (SCC) 2019 (Novotel in Aachen, Germany) 2019.06

Research paper (international conference proceedings), Accepted

Data-Based Model-Predictive Control of a Turbocharged SI-Engine with Low Pressure EGR

Martin Keller, Daichi Sakai, Matthias Wehr, Dirk Abel (Institute for Automatic Control, RWTH Aachen University), Severin Geiger, Marco Günther, Stefan Pischinger (Institute for Combustion Engines, RWTH Aachen University). Hiromitsu Ohmori (Department of System Engineering, Keio University)

Symposium for Combustion Control (SCC) 2019 (Novotel in Aachen) 2019.06

Research paper (international conference proceedings), Accepted

Simple Adaptive Control for a Diesel Engine Air Path System

Eguchi M., Zhang X., Sakai D., Ohmori H., Hayashi T., Hirata M., Takahashi M., Yamasaki Y., Kaneko S.

2019 12th Asian Control Conference, ASCC 2019 (2019 12th Asian Control Conference, ASCC 2019) 103 - 107 2019.06

ISSN 9784888983006

Solar parabolic trough thermal energy output forecasting based on K-Nearest Neighbors approach

Jafferi Jamaludin and Hiromitsu Ohmori,

2019 the 3rd International Conference on Sustainable Energy Engineering (ICSEE 2019) (Shanghai China) 2019.05

Research paper (international conference proceedings), Accepted

Subspace-Based Algorithms for Localization and Tracking of Multiple Near-Field Sources

Zuo W., Xin J., Ohmori H., Zheng N., Sano A.

IEEE Journal on Selected Topics in Signal Processing (IEEE Journal on Selected Topics in Signal Processing) 13 ( 1 ) 156 - 171 2019.03

ISSN 19324553

© 2007-2012 IEEE. In this paper, we investigate the problems of estimating and tracking the location parameters [i.e., directions-of-arrival (DOAs) and ranges] of multiple near-field (NF) narrowband sources impinging on a symmetric uniform linear array, and a simple subspace-based algorithm for localization of NF sources (SALONS) is presented, where the computationally burdensome eigendecomposition and spectrum peak searching are avoided. In the SALONS, the DOAs and ranges are estimated separately with a one-dimensional subspace-based estimation technique, where the null spaces are obtained through the linear operation of the correlation matrices formed from the antidiagonal elements of the noiseless array covariance matrix, and the estimated DOAs and ranges are automatically paired without any additional procedure. Then the statistical analysis of the presented batch SALONS is studied, and the asymptotic mean-squared-error expressions of the estimated DOAs and ranges are derived. Furthermore, an online algorithm is developed for tracking the multiple moving NF sources with crossover points on their trajectories. The effectiveness and the theoretical analysis of the presented algorithms are verified through numerical examples, and the simulation results show that the proposed algorithms provide good estimation and tracking performance for DOAs and show satisfactory estimation and tracking performance for ranges.

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小脳演算モデルコントローラを用いたフィードバック誤差学習によるディーゼルエンジンの燃焼制御

江口誠、大森浩充、高橋幹, 山崎由大、金子成彦

自動車技術会論文集 (自動車技術会) 2019.01

Research paper (scientific journal), Joint Work, Accepted

Localization of Near-Field Sources Based on Linear Prediction and Oblique Projection Operator

Weiliang Zuo, Jingmin Xin (Xi’an Jiaotong Univ.), Hiromitsu Ohmori (Keio Univ.), Nanning Zheng (Xi’an Jiaotong Univ.), and Akira Sano (Kieo Univ.)

IEEE Transactions on Signal Processing (IEEE) 67 ( 2 ) 415 - 430 2019.01

Accepted, ISSN 941-0476

© 1991-2012 IEEE. This paper investigates the localization of multiple near-field narrowband sources with a symmetric uniform linear array, and a new linear prediction approach based on the truncated singular value decomposition (LPATS) is proposed by taking an advantage of the anti-diagonal elements of the noiseless array covariance matrix. However, when the number of array snapshots is not sufficiently large enough, the 'saturation behavior' is usually encountered in most of the existing localization methods for the near-field sources, where the estimation errors of the estimated directions-of-arrival (DOAs) and ranges cannot decrease with the signal-to-noise ratio. In this paper, an oblique projection based alternating iterative scheme is presented to improve the accuracy of the estimated location parameters. Furthermore, the statistical analysis of the proposed LPATS is studied, and the asymptotic mean-square-error expressions of the estimation errors are derived for the DOAs and ranges. The effectiveness and the theoretical analysis of the proposed LPATS are verified through numerical examples, and the simulation results show that the LPATS provides good estimation performance for both the DOAs and ranges compared to some existing methods.

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Evaluation for Maximum Hosting Capacity of Distributed Generation considering Active Network Management

Ikeda S., Ohmori H.

International Journal of Electrical and Electronic Engineering and Telecommunications (International Journal of Electrical and Electronic Engineering and Telecommunications) 7 ( 3 ) 96 - 102 2018.07

© 2018 Int. J. Elec. & Elecn. Eng. & Telcomm. With the increasing penetration of renewable Distributed Generation (DG), it is important to assess the Maximum Hosting Capacity (MHC) in active distribution networks. Active Network Management (ANM) such as coordinated voltage control, reactive power compensation, DG curtailment, DG power factor control, network reconfiguration and demand response can play an important role in increasing the MHC. The MHC evaluation problem considering all the above elements of ANM can be formulated as a mixed integer nonlinear programming model. However, this original nonconvex model cannot guarantee convergence to optimality. This paper proposes the mixed integer second-order cone programming model for evaluating the MHC, by using exact linearization and second-order cone relaxation. The modified IEEE 33-bus test system is used to demonstrate the effectiveness of the proposed model and analyze the effect of each ANM element on the MHC increase. The results show that when considering all the above elements of ANM, the gain of the MHC is greater than 62%.

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Optimal sizing of photovoltaic systems for loss minimization in distribution network

Ikeda S., Takeda A., Ohmori H.

SICE ISCS 2018 - 2018 SICE International Symposium on Control Systems (SICE ISCS 2018 - 2018 SICE International Symposium on Control Systems) 2018-January 185 - 192 2018.04

ISSN 9784907764586

© 2018 The Society of Instrument and Control Engineers - SICE. The use of photovoltaics (PV) in electric power networks has increased because of advantages such as power loss reduction, environmental friendliness, voltage profile improvement, and postponement of system upgrades. However, using PVs of an inappropriate size leads to greater power losses due to variations in PV outputs and demand loads. Therefore, it is necessary to determine the optimal size of PVs. When one considers the various weather conditions and demand load profiles, the optimal PV sizing problem (OPSP) becomes a large-scale optimization that is difficult to solve. In this paper, to resolve this computational issue, we formulate the OPSP as a second-order cone programming model and propose a decomposition using the subgradient method for solving the partial Lagrangian dual problem. We implemented the proposed method on a 47-bus distribution feeder model, and the simulation results proved its viability.

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Diesel Engine Combustion Control using Feedback Error Learning with Artificial Intelligence-Feedforward Controller

OHMORI HIROMITSU

自動車技術会論文集 (自動車技術会) 49 ( 2 ) 230 - 234 2018.03

Research paper (scientific journal), Joint Work, Accepted

現在のディーゼルエンジン燃焼制御は, 静的マップによるフィードフォワード制御を行うことが主流である．本研究では，フィードバック誤差学習（FEL)の制御構造を保存して，フィードフォワード制御器をAI（人工知能）の技術を用いてオンライン適応・学習させ，ドライバーや環境に積極的に適応・学習できる制御系を提案している．設計された制御アルゴリズムの有効性を確認するために，東大離散化ディーゼルエンジンモデルに対する数値シミュレーションと東大エンジンベンチによる実証実験実施する．

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Online Parameter Estimation for Lithium-ion Battery by using Adaptive Observer for Fractional Order System

Naohiro Takamatsu、OHMORI HIROMITSU

Electronics and Communications in Japan (2018 Wiley Periodicals, Inc.) 101 ( 3 ) 80 - 89 2018.01

Research paper (scientific journal), Joint Work, Accepted, ISSN 19429533

Due to the prevalence of Li‐ion battery, the importance of the battery management system (BMS) is increasing. BMS is the system for managing the operation of batteries and monitoring their state of health. By using the observer containing parameter estimator for analyzing the equivalent circuit model of batteries, the online diagnosis of the batteries becomes possible. However, the Li‐ion battery has complicated dynamics derived from the Warburg impedance, which described the diffusion phenomena of the Li‐ion. Applying fractional calculus to the expression of the system, the dynamics of Warburg impedance can be described simply. By designing the adaptive observer which can treat the system described as fractional‐order system, it is expected to become possible to identify equivalent circuit containing Warburg element online without approximation. In this paper, we designed the Kreisselmeier‐type adaptive observer for the linear fractional‐order system. Then, we applied the proposed observer to the half‐cell of the lithium‐ion battery modeled by Randles circuit under semi‐infinite linear diffusion, and confirm the effectiveness of proposed adaptive observer by numerical simulation.

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Diesel Engine Combustion Control Based on Cerebellar Model Articulation Controller (CMAC) in Feedback Error Learning

Zhang X., Eguchi M., Ohmori H.

IFAC-PapersOnLine (IFAC-PapersOnLine) 51 ( 31 ) 516 - 521 2018

© 2018 The trend started in 1997 with the introduction of common rail injection and after some protocols set new targets for overall CO2 emissions. As the diesel engine emits less CO2 than its gasoline counterpart, it kept conquering more and more market shares. Conventional diesel engine control design is mainly based on the maps techniques which required too much time, money and human resources under the number of experiments under various environmental conditions. This makes increasing system complexity. In our authors group, we have proposed that the control structure has the feedback error learning, two-degree-of-freedom controller configuration, with advanced neural networks (NNs) as the feedforward controller along the model-based control method. On the other hand, a cerebellar model articulation controller (CMAC) is a non-fully connected perceptron like associative memory network with overlapping receptive fields, which is used to resolve problems that involve rapid growth and the learning difficulty. Then CMACs have the advantages of good generalization capability, fast learning ability, and simple computation. To our best knowledge, this is new introduce the cerebellar model articulation controller (CMAC) for the control diesel engine combustion control. The effectiveness of the proposed method will be confirmed through numerical simulations based on the Tokyo University diesel engine model with triple fuel injections.

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