Masaki Ogura

Research

Control of Fish School

A typical mathematical model of schooling fish involves an attraction/alignment/repulsion law, which is not necessarily well-considered in the current systems and control theory. In our research project, we are developing theories for the analysis and control of fish schooling models.

References
[1] M. Ogura and N. Wakamiya, “Reduced order model predictive control of a fish schooling model,” Submitted for publication, 2021.


Shepherding

Shepherding problems refer to a problem of guiding a flock of agents from an initial location to an objective location by fewer external entities, and have several potential applications such as robotic agents to herd sheep and crowd control. We are developing novel algorithms for the shepherding of heterogeneous agents.

Proposed algorithm
Farthest Agent Targeting
References
[1] R. Himo, M. Ogura, and N. Wakamiya, “Shepherding algorithm for agents with heterogeneous sensitivities,” in 4th International Symposium on Swarm Behavior and Bio-Inspired Robotics 2021 (to be presented), 2021.


Deep Unfolding for Model-Based Control (TAFCREST

We are developing model-based controller synthesis framework by utilizing the novel machine learning technique called deep unfolding. We are finding that our approach is quite effective for the control of various classes of dynamical systems including systems with saturations, delay systems, and systems with stochastic noises.

References
[2] K. Kobayashi, M. Ogura, T. Kobayashi, and K. Sugimoto, “Deep unfolding-based output feedback control design for linear systems with input saturation,” in SICE International Symposium on Control Systems 2021, 2021, pp. 2A1-5. [ arXiv ]
[1] M. Kishida*, M. Ogura*, Y. Yoshida, and T. Wadayama, “Deep learning-based average consensus,” IEEE Access, vol. 8, pp. 142404 - 142412, 2020. (*equal contribution) [ DOI | arXiv | http ]


Epidemics Control in Social Networks (JSPS Grant-in-Aid for Early-Career Scientists)

Due to the current pandemic of COIVD-19, the containment of epidemic processes taking place in social networks is a critical problem of both theoretical and practical interest. Because the vaccines are not yet fully available (as of Mar 16th, 2021), we still need to rely on taking social distances. This social distancing strategy can be regarded as a feedback control on the epidemic processes, as the degree of social distancing is in positive corelation with the disease spread. In our research group, we are leveraging systems and control theory to develop novel theoretical frameworks for the prediction and containment of epidemic spreading processes over complex networks.

Slides
M. Ogura, “Modelling, analysis, and control of networked epidemic processes,” CiNet Friday Lunch Seminar, 2020.
References
[2] Y. Onoue, K. Hashimoto, M. Ogura, and T. Ushio, “Event-triggered control for mitigating SIS spreading processes,” Submitted for publication, 2020. [ arXiv ]
[1] M. Ogura and V. M. Preciado, “Stability of spreading processes over time-varying large-scale networks,” IEEE Transactions on Network Science and Engineering, vol. 3, no. 1, pp. 44-57, 2016. Runner-up of 2019 IEEE TNSE Best Paper Award. [ DOI | arXiv | http ]


Positive Systems(NII Open Collaborative Research

Positive systems refer to, roughly speaking, the class of dynamical systems, whose response signals to nonnegative input signals are constrained to be nonnegative and have applications in various areas, including pharmacology, epidemiology, population biology, and communication networks. In our research group, we are developing a novel mathematical framework for optimizing positive systems with Geometric Programming. The framework is applicable to several problems of theoretical interest such as H2 and H-infinity optimizations as well as optimization under time-delays and structured uncertainties.

Slides
M. Ogura, “Optimization of positive linear systems via geometric programming,” Shenzhen University, 2019.
References
[2] M. Ogura, M. Kishida, and J. Lam, “Geometric programming for optimal positive linear systems,” IEEE Transactions on Automatic Control, vol. 65, no. 11, pp. 4648-4663, 2020. [ DOI | arXiv | http ]
[1] C. Zhao, M. Ogura, and K. Sugimoto, “Stability optimization of positive semi-Markov jump linear systems via convex optimization,” SICE Journal of Control, Measurement, and System Integration, vol. 13, no. 5, pp. 233-239, 2020. [ DOI | arXiv | http ]


Control Theory meets with Design Engineering(NII Open Collaboration Research

Projects are indispensable and central in most of the industries for performing several types of work (PMI 2013). For this reason, project management has been one of the major research themes in the feld of engineering design during the last half-century. In our research project, by leveraging theoretical results about positive systems and switched systems in the systems and control theory, we are developing an optimization framework for making a cost-efcient investment in design rules when the underlying dependency structure between modules is changing over time.

Slides
M. Ogura, M. Kishida, and A. Yassine, “Optimizing product development projects under asynchronous and aperiodic system-local interactions,” in 21st International DSM Conference, 2019, pp. 97-106.
References
[2] C. Zhao, M. Ogura, M. Kishida, and A. Yassine, “Optimal resource allocation for dynamic product development process via convex optimization,” Research in Engineering Design, vol. 32, no. 1, pp. 71-90, 2021. [ DOI | arXiv | http ]
[1] M. Ogura, J. Harada, M. Kishida, and A. Yassine, “Resource optimization of product development projects with time-varying dependency structure,” Research in Engineering Design, vol. 30, no. 3, pp. 435-452, 2019. [ DOI | arXiv | http ]