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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| EE | 2023-01-19 15:40 |
Fukuoka | Kyushu Institute of Technology (Primary: On-site, Secondary: Online) |
A Study on Model Predictive Control DC-DC Converter Using Dynamic Quantization Kohei Yamamoto, Hidenori Maruta (Nagasaki Univ.)  EE2022-39 |
Model predictive control of DC-DC converters is a control method that requires a large amount of computation for predict... [more] | EE2022-39 pp.72-77 |
| CAS, SIP, VLD, MSS | 2022-06-16 10:50 |
Aomori | Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
Multi-Agent Surveillance Based on Equitability of Travel Costs Kyohei Murakata, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) CAS2022-3 VLD2022-3 SIP2022-34 MSS2022-3 |
In this paper, we consider the surveillance problem by multiple agents. A surveillance area is modeled by a directed gra... [more] | CAS2022-3 VLD2022-3 SIP2022-34 MSS2022-3 pp.13-16 |
| RCS, SIP, IT | 2022-01-20 16:15 |
Online | Online | [Invited Talk]
When Deep Unfolding Meets Control Engineering Masaki Ogura (Osaka Univ.) IT2021-45 SIP2021-53 RCS2021-213 |
Deep unfolding is a technique for tuning parameters for accelerating the convergence of iterative algorithms, and has be... [more] | IT2021-45 SIP2021-53 RCS2021-213 p.95 |
| SS, MSS | 2022-01-11 17:05 |
Nagasaki | Nagasakiken-Kensetsu-Sogo-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
Scalable Model Predictive Control of Energy Management Systems Based on Human Behavior Change Shogo Shimamoto, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) MSS2021-43 SS2021-30 |
In this paper, we consider the incorporation of human decision making into an energy management system. Here, we conside... [more] | MSS2021-43 SS2021-30 pp.70-73 |
| MSS, CAS, IPSJ-AL [detail] | 2021-11-19 11:45 |
Online | Online | Multi-Agent Surveillance Based on Travel Cost Minimization Kyohei Murakata, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) CAS2021-50 MSS2021-30 |
In this paper, we consider the surveillance problem by multiple agents. A surveillance area is modeled by a directed gra... [more] | CAS2021-50 MSS2021-30 pp.76-79 |
| ITS, IEE-ITS, IPSJ-ITS | 2021-09-07 13:30 |
Online | Online | Optimal Signal Control Based on Genetic Algorithm for an Ultradiscrete Traffic Flow Model in order for Reduction of Traffic Jams Yuuki Aoki, Tatsuya Kai (Tokyo Univ. of Science) ITS2021-6 |
The purpose of this study is to reduce total number of traffic jams of an ultradiscrete traffic flow model by controllin... [more] | ITS2021-6 pp.7-11 |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-14 16:35 |
Online | Online | [Invited Talk]
Optimal Control of Multi-Agent Systems: Surveillance Problem and Vehicle Platooning Koichi Kobayashi (Hokkaido Univ.) RCC2021-29 NS2021-39 RCS2021-84 SR2021-27 SeMI2021-15 |
In this talk, our results on control of multi-agent systems are introduced. First, the surveillance problem is introduce... [more] | RCC2021-29 NS2021-39 RCS2021-84 SR2021-27 SeMI2021-15 p.36(RCC), p.38(NS), p.38(RCS), p.41(SR), p.20(SeMI) |
| SIP, CAS, VLD, MSS | 2021-07-05 16:25 |
Online | Online | Thermal Comfort Aware Real-time Co-scheduling of HVAC, Battery System, and Smart Appliances for Smart Building Daichi Watari, Ittetsu Taniguchi (Osaka Univ.), Francky Catthoor (IMEC/KUL), Charalampos Marantos (NTUA), Kostas Siozios (AUTH), Elham Shirazi (IMEC/KUL), Dimitrios Soudris (NTUA), Takao Onoye (Osaka Univ.) CAS2021-8 VLD2021-8 SIP2021-18 MSS2021-8 |
Building energy management is vital for reducing electricity costs and maximizing occupant comfort. This paper proposes ... [more] | CAS2021-8 VLD2021-8 SIP2021-18 MSS2021-8 pp.36-41 |
| NLP, CCS | 2021-06-11 13:55 |
Online | Online | A Blending Stabilization Method of Discrete Mechanics and Nonlinear Optimization for 2-dimensional Nonlinear Films Makoto Koike, Tatsuya Kai (Tokyo Univ. of Science) NLP2021-7 CCS2021-7 |
The aim of this study is to develop a stabilization control method for 2-dimensional nonlinear film, which is one of th... [more] | NLP2021-7 CCS2021-7 pp.28-33 |
| NLP, MSS (Joint) |
2021-03-15 14:30 |
Online | Online | Design of Model Predictive-Based Demand Response Utilizing Price Information Masafumi Murata, Koichi Kobayashi (Hokkaido Univ.), Shun-ichi Azuma (Nagoya Univ.), Nobuyuki Yamaguchi (Tokyo Univ. of Science), Yuh Yamashita (Hokkaido Univ.) MSS2020-46 |
In this paper, we propose a method of demand response (DR) based on model predictive control. In the authors' previous m... [more] | MSS2020-46 pp.14-17 |
| NLP, MSS (Joint) |
2021-03-15 14:55 |
Online | Online | Control of Energy Management Systems via Human Decision-Making Models Using Markov Chains Shogo Shimamoto, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) MSS2020-47 |
In this paper, we consider the incorporation of human decision making into an energy management system. Here, we conside... [more] | MSS2020-47 pp.18-21 |
| NLP, MSS (Joint) |
2021-03-16 09:15 |
Online | Online | Modeling Inter-sector Air Traffic Flow and Congestion Degree Prediction Ryosuke Mishima, Kunihiko Hiraishi (JAIST) MSS2020-49 |
In 2015, the Ministry of Land, Infrastructure and Transportation have started to provide information on aircraft flying ... [more] | MSS2020-49 pp.27-32 |
| RCC | 2021-01-22 13:30 |
Online | Online | Maximum Turn-off Control Based on Block-sparse Optimization and Its Feedback Control Takumi Iwata, Shun-ichi Azuma, Ryo Ariizumi, Toru Asai (Nagoya Univ.) RCC2020-34 |
In this paper, maximum turn-off control and its feedback control are considered. Maximum turn-off control is, in the cas... [more] | RCC2020-34 pp.1-3 |
| ITS, WBS, RCC | 2020-12-14 10:20 |
Online | Online | A study on joint optimization of control input and communication scheduling in IEEE 802.15.4 network Masashi Shiota, Koji Ishii (Kagawa Univ) WBS2020-10 ITS2020-6 RCC2020-13 |
When applying IEEE 802.15.4 beacon mode into the wireless networked control system (WNCS) with multiple– plants, individ... [more] | WBS2020-10 ITS2020-6 RCC2020-13 pp.13-18 |
| MSS, CAS, IPSJ-AL [detail] | 2020-11-26 15:50 |
Online | Online | Model Predictive Control of Energy Management Systems with Human Decision Making Shogo Shimamoto, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) CAS2020-35 MSS2020-27 |
It is important to consider human decision making in order to control energy consumption. In this paper, we consider hum... [more] | CAS2020-35 MSS2020-27 pp.91-95 |
| IBISML | 2020-10-21 11:05 |
Online | Online | IBISML2020-20 |
As complexity of robots and environments increases, analytically formulating their kinematics and dynamics becomes diffi... [more] | IBISML2020-20 pp.37-38 |
| PN, NS, OCS (Joint) |
2020-06-18 13:40 |
Online | Online | Optimal VNF Management with Model Predictive Control for Multiple Service Chains Masaya Kumazaki (Univ. Fukui), Masaki Ogura (Osaka Univ.), Takuji Tachibana (Univ. Fukui) NS2020-22 |
Network function virtualization (NFV) provides network functions by implementing virtual network function (VNF) on a com... [more] | NS2020-22 pp.1-6 |
| EE | 2020-01-15 10:50 |
Kagoshima | HOUZAN HALL | A study on influence of prediction horizon of model predictive control to characteristics of digitally controlled dc-dc converter Yuya Noda, Koya Taguchi, Hidenori Maruta (Nagasaki Univ.) EE2019-51 |
In this paper, we evaluate influence of a prediction horizon with combinatorial approach of the model predictive control... [more] | EE2019-51 pp.13-18 |
| RISING (2nd) |
2019-11-26 14:10 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Poster Presentation]
Optimal VNF Placement and Route Selection with Model Predictive Control for Service Chains Masaya Kumazaki (Univ. Fukui), Masaki Ogura (Osaka Univ.), Takuji Tachibana (Univ. Fukui) |
Network function virtualization (NFV) provides network functions by implementing virtual network function (VNF) on a com... [more] | |
| EE, IEE-SPC | 2019-07-24 11:30 |
Hiroshima | A Study on Model Predictive Control for DC-DC Converters with Combinatorial Approach Yuya Noda, Hidenori Maruta (Nagasaki Univ.) EE2019-19 |
In this paper, we propose a model predictive control (MPC) method for dc-dc converters with combinatorial approach. One ... [more] | EE2019-19 pp.13-18 |
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