• 谷歌学术引用
• ORCiD

预印本

[8]	Q. Wang, Y. Bai, M. Ogura, and L. Peng, “Periodic event-triggered generalized dissipative state estimation for hidden semi-Markov jump systems,” Submitted for publication.
[7]	R. Nagai, Y. Bai, M. Ogura, S. Kotsuki, and N. Wakamiya, “Evaluation of effectiveness of intervention strategy in control simulation experiment through comparison with model predictive control,” Submitted for publication.
[6]	Y. Deng, Y. Bai, Y. Wang, M. Ogura, and M. Feroskhan, “Safe adaptive control for uncertain systems with complex input constraints,” Submitted for publication. [ arXiv | http ]
[5]	T. Ohtsuka, A. Okazaki, M. Ogura, and S. Kotsuki, “Convex optimization of initial perturbations toward quantitative weather control,” Submitted for publication. [ arXiv | http ]
[4]	Q. Wang, Y. Bai, M. Ogura, and L. Peng, “Self-triggered energy-to-peak filtering for semi-Markov jump systems with incomplete semi-Markov kernel,” Submitted for publication.
[3]	C. Zhao, K. Sakurama, and M. Ogura, “Optimal toll strategy for traffic flow network: A geometric programming approach,” Under preparation.
[2]	Q. Wang, Y. Bai, M. Ogura, and L. Peng, “Dynamic self-triggered filtering for semi-Markov jump systems under delayed mode information,” Submitted for publication.
[1]	Q. Wang, Y. Bai, L. Peng, J. Lam, M. Ogura, and N. Wakamiya, “A novel distributed consensus filtering method via deep unfolding,” Submitted for publication.

书籍章节

[4]	K. Sakurama, K. Kashima, T. Ikeda, N. Hayashi, K. Hoshino, M. Ogura, and C. Zhao, “System-Control-Based Approach to Car-Sharing Systems,” in Advanced Mathematical Science for Mobility Society. Springer Singapore, 2024, pp. 127-171. [ DOI | http ]
[3]	V. M. Preciado, M. Zargham, C. Nowzari, S. Han, M. Ogura, A. Jadbabaie, and G. J. Pappas, “Bio-inspired Framework for Allocation of Protection Resources in Cyber-Physical Networks,” in Principles of Cyber-Physical Systems. Cambridge University Press, 2020, pp. 293-322. [ DOI | arXiv | http ]
[2]	M. Ogura and V. M. Preciado, “Optimal Containment of Epidemics in Temporal and Adaptive Networks,” in Temporal Networks Epidemiology. Springer, 2017, pp. 241-266. [ DOI | arXiv | http ]
[1]	M. Ogura and C. F. Martin, “Linear Switching Systems and Random Products of Matrices,” in Mathematical System Theory - Festschrift in Honor of Uwe Helmke on the Occasion of his Sixtieth Birthday, K. Hüper and J. Trumpf, Eds. CreateSpace, 2013, pp. 291-300.

受邀讲话

[12]	“Shepherding as a paradigm for swarm control,” 2024 IEEE International Conference on Cyborg and Bionic Systems, 2024.
[11]	“Enhancing Control System Design through Deep Unfolding: A Systematic Approach,” University of Hawaii at Manoa, 2023. [ http ]
[10]	“Perspectives on Artificial Intelligence,” 2nd Japanese-Canadian Frontiers of Science (JCFoS) Symposium, 2023. [ http ]
[9]	“When deep unfolding meets control engineering,” 37th International Technical Conference on CircuitsSystems, Computers and Communications, 2022. [ http ]
[8]	“Optimization of positive linear systems via geometric programming,” Guandong University of Technology, 2019.
[7]	“Optimization of positive linear systems via geometric programming,” Shenzhen University, 2019. [ http ]
[6]	“Synthesis of positive linear systems by geometric programming,” University of Hong Kong, 2019. [ http ]
[5]	“Network epidemiology and control theory,” University of Hong Kong, 2018. [ http ]
[4]	“Analysis and control of spreading processes over complex networks,” Washington State University, 2017.
[3]	“Analysis and control of spreading processes over complex networks,” Tokyo University of Agriculture and Technology, 2016. [ http ]
[2]	“Stability analysis of switched linear systems with non-traditional switching signals,” in GRASP special seminar, University of Pennsylvania, 2014. [ http ]
[1]	“Mean stability of switched linear systems,” Université Catholique de Louvain, 2013. [ http ]

期刊文章

[54]	A. Fujioka, M. Ogura, and N. Wakamiya, “Cyclic pursuit formation control for arbitrary desired shapes,” Journal of the Franklin Institute, vol. 362, no. 2, p. 107467, 2025. [ DOI | arXiv | http ]
[53]	Y. Bai, P. T. T. Ngoc, H. D. Nguyen, D. L. Le, Q. H. Ha, K. Kai, Y. X. S. To, Y. Deng, J. Song, N. Wakamiya, H. Sato, and M. Ogura, “Swarm navigation of cyborg-insects in unknown obstructed soft terrain,” Nature Communications (accepted for publication), 2024. [ arXiv ]
[52]	J. Aizawa, M. Ogura, M. Shimono, and N. Wakamiya, “Firing pattern manipulation of neuronal networks by deep unfolding‐based model predictive control,” IET Control Theory & Applications, vol. 18, no. 15, pp. 2003-2013, 2024. [ DOI | http ]
[51]	A. Li, M. Ogura, and N. Wakamiya, “Swarm shepherding using bearing-only measurements,” Philosophical Transactions of the Royal Society A (accepted for publication), vol. 383, p. 20240145, 2024. [ DOI ]
[50]	C. Zhao, B. Zhu, M. Ogura, and J. Lam, “Probability rate optimization of positive Markov jump linear systems via DC programming,” Asian Journal of Control, vol. 26, no. 5, pp. 2242-2249, 2024. [ DOI | http ]
[49]	W. Imahayashi, Y. Tsunoda, and M. Ogura, “Route design in sheepdog system–traveling salesman problem formulation and evolutionary computation solution–,” Advanced Robotics, vol. 38, no. 9-10, pp. 632-646, 2024. [ DOI | arXiv | http ]
[48]	J. J. R. Liu, M. Ogura, Q. Li, and J. Lam, “Learning-based stabilization of Markov jump linear systems,” Neurocomputing, vol. 584, p. 127618, 2024. [ DOI | http ]
[47]	R. Liu, M. Ogura, E. F. Dos Reis, and N. Masuda, “Effects of concurrency on epidemic spreading in Markovian temporal networks,” European Journal of Applied Mathematics, vol. 35, no. 3, pp. 430-461, 2024. [ DOI | arXiv | http ]
[46]	C. Zhao, K. Sakurama, and M. Ogura, “Optimization of buffer networks via DC programming,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 70, no. 2, pp. 606-610, 2023. [ DOI | http ]
[45]	M. Ogura and C. F. Martin, “Mean escape time of switched Riccati differential equations,” Journal of the Franklin Institute, vol. 360, no. 10, pp. 6827-6845, 2023. [ DOI | arXiv | http ]
[44]	M. Ogura and N. Wakamiya, “Reduced-order model predictive control of a fish schooling model,” Nonlinear Analysis: Hybrid Systems, vol. 49, p. 101342, 2023. [ DOI | arXiv | http ]
[43]	C. Zhao, B. Zhu, M. Ogura, and J. Lam, “Parameterized synthesis of discrete-time positive linear systems: A geometric programming perspective,” IEEE Control Systems Letters, vol. 7, pp. 2551-2556, 2023. [ DOI | http ]
[42]	X. Gong, M. Ogura, J. Shen, T. Huang, and Y. Cui, “Optimal epidemics policy seeking on networks-of-networks under malicious attacks by geometric programming,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 53, no. 6, pp. 3845-3857, 2023. [ DOI | http ]
[41]	M. Ogura and C. Nowzari, “Special issue: modeling, analysis, and control of epidemics in networks,” Mathematical Biosciences and Engineering, vol. 20, no. 5, pp. 8446-8447, 2023. [ DOI | http ]
[40]	A. Li, M. Ogura, and N. Wakamiya, “Communication-free shepherding navigation with multiple steering agents,” Frontiers in Control Engineering, vol. 4, 2023. [ DOI | arXiv | http ]
[39]	A. Fujioka, M. Ogura, and N. Wakamiya, “Shepherding algorithm for heterogeneous flock with model-based discrimination,” Advanced Robotics, vol. 37, no. 1-2, pp. 99-114, 2023. [ DOI | arXiv | http ]
[38]	B. Zhu, J. Lam, and M. Ogura, “Log-log convexity of an optimal control problem for positive linear systems,” Automatica, vol. 146, p. 110553, 2022. [ DOI | http ]
[37]	M. Nagahara, M. Ogura, and Y. Yamamoto, “Iterative greedy LMI for sparse control,” IEEE Control Systems Letters, vol. 6, pp. 986-991, 2022. [ DOI | http ]
[36]	M. Kumazaki, M. Ogura, and T. Tachibana, “Dynamic service chain construction based on model predictive control in NFV environments,” IEICE Transactions on Communications, vol. E105-B, no. 4, pp. 399-410, 2022. [ DOI | http ]
[35]	M. Kishida* and M. Ogura*, “Temporal deep unfolding for constrained nonlinear stochastic optimal controls,” IET Control Theory & Applications, vol. 16, no. 2, pp. 139-150, 2022. (*equal contribution) [ DOI | http ]
[34]	R. Himo, M. Ogura, and N. Wakamiya, “Iterative algorithm for shepherding unresponsive sheep,” Mathematical Biosciences and Engineering, vol. 19, no. 4, pp. 3509-3525, 2022. [ DOI | http ]
[33]	T. Kimura and M. Ogura, “Distributed 3D deployment of aerial base stations for on-demand communication,” IEEE Transactions on Wireless Communications, vol. 20, no. 12, pp. 7728-7742, 2021. [ DOI | http ]
[32]	K. Hashimoto, Y. Onoue, M. Ogura, and T. Ushio, “Event-triggered control for mitigating SIS spreading processes,” Annual Reviews in Control, vol. 52, pp. 479-494, 2021. [ DOI | arXiv | http ]
[31]	K. Sugimoto, T. Aihara, M. Ogura, and K. Hanada, “Gain scheduling for sampled-data state estimation over lossy networks,” Transactions of the Institute of Systems, Control and Information Engineers, vol. 34, no. 11, pp. 287-293, 2021. [ DOI | http ]
[30]	M. Nagahara, B. Krishnamachari, M. Ogura, A. Ortega, Y. Tanaka, Y. Ushifusa, and T. W. Valente, “Control, intervention, and behavioral economics over human social networks against COVID-19,” Advanced Robotics, vol. 35, no. 11, pp. 733-739, 2021. [ DOI | http ]
[29]	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 ]
[28]	X. Chen, M. Ogura, and V. M. Preciado, “SDP-Based moment closure for epidemic processes on networks,” IEEE Transactions on Network Science and Engineering, vol. 7, no. 4, pp. 2850-2865, 2020. [ DOI | http ]
[27]	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 ]
[26]	W. Mei, C. Zhao, M. Ogura, and K. Sugimoto, “Mixed H2/H∞ control of delayed Markov jump linear systems,” IET Control Theory & Applications, vol. 14, no. 15, pp. 2076-2083, 2020. [ DOI | arXiv | http ]
[25]	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 ]
[24]	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 ]
[23]	N. Masuda, V. M. Preciado, and M. Ogura, “Analysis of the susceptible-infected-susceptible epidemic dynamics in networks via the non-backtracking matrix,” IMA Journal of Applied Mathematics, vol. 85, no. 2, pp. 214-230, 2020. [ arXiv | http ]
[22]	X. Chen, M. Ogura, and V. M. Preciado, “Bounds on the spectral radius of digraphs from motif counts,” SIAM Journal on Matrix Analysis and Applications, vol. 41, no. 2, pp. 525-553, 2020. [ DOI | http ]
[21]	M. Ogura and V. M. Preciado, “Stability of SIS spreading processes in networks with non-Markovian transmission and recovery,” IEEE Transactions on Control of Network Systems, vol. 7, no. 1, pp. 349-359, 2020. [ DOI | arXiv | http ]
[20]	M. Ogura, W. Mei, and K. Sugimoto, “Synergistic effects in networked epidemic spreading dynamics,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 67, no. 3, pp. 496-500, 2020. [ DOI | arXiv | http ]
[19]	Y. Abe, M. Ogura, H. Tsuji, A. Miura, and S. Adachi, “Resource and network management framework for a large-scale satellite communications system,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E103, no. 2, pp. 492-501, 2020. Telecom System Technology Student Award, Telecommunication Advancement Foundation. [ DOI | http ]
[18]	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 ]
[17]	M. Ogura, V. M. Preciado, and N. Masuda, “Optimal containment of epidemics over temporal activity-driven networks,” SIAM Journal on Applied Mathematics, vol. 79, no. 3, pp. 986-1006, 2019. [ DOI | arXiv | http ]
[16]	W. Mei and M. Ogura, “Kronecker weights for instability analysis of Markov jump linear systems,” IET Control Theory & Applications, vol. 13, no. 3, pp. 360-366, 2019. [ DOI | arXiv | http ]
[15]	M. Wakaiki, M. Ogura, and J. P. Hespanha, “LQ-optimal sampled-data control under stochastic delays: gridding approach for stabilizability and detectability,” SIAM Journal on Control and Optimization, vol. 56, no. 4, pp. 2634-2661, 2018. [ DOI | arXiv | http ]
[14]	M. Ogura, A. Cetinkaya, T. Hayakawa, and V. M. Preciado, “State feedback control of Markov jump linear systems with hidden-Markov mode observation,” Automatica, vol. 89, pp. 65-72, 2018. [ DOI | arXiv | http ]
[13]	M. Ogura and V. M. Preciado, “Second-order moment-closure for tighter epidemic thresholds,” Systems & Control Letters, vol. 113, pp. 59-64, 2018. [ DOI | arXiv | http ]
[12]	M. Ogura and V. M. Preciado, “Optimal design of switched networks of positive linear systems via geometric programming,” IEEE Transactions on Control of Network Systems, vol. 4, no. 2, pp. 213-222, 2017. [ DOI | arXiv ]
[11]	M. Ogura, M. Wakaiki, H. Rubin, and V. M. Preciado, “Delayed bet-hedging resilience strategies under environmental fluctuations,” Physical Review E, vol. 95, p. 052404, 2017. [ DOI | arXiv | http ]
[10]	M. Ogura, V. M. Preciado, and R. M. Jungers, “Efficient method for computing lower bounds on the p-radius of switched linear systems,” Systems & Control Letters, vol. 94, pp. 159-164, 2016. [ DOI | arXiv | http ]
[9]	M. Ogura and V. M. Preciado, “Epidemic processes over adaptive state-dependent networks,” Physical Review E, vol. 93, p. 062316, 2016. [ DOI | arXiv | http ]
[8]	M. Ogura and V. M. Preciado, “Stability of Markov regenerative switched linear systems,” Automatica, vol. 69, pp. 169-175, 2016. [ DOI | arXiv | http ]
[7]	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 ]
[6]	M. Ogura and C. F. Martin, “Stability analysis of linear systems subject to regenerative switchings,” Systems & Control Letters, vol. 75, pp. 94-100, 2015. [ DOI | http ]
[5]	M. Ogura and C. F. Martin, “A limit formula for joint spectral radius with p-radius of probability distributions,” Linear Algebra and its Applications, vol. 458, pp. 605-625, 2014. [ DOI | arXiv | http ]
[4]	M. Ogura and C. F. Martin, “Stability analysis of positive semi-Markovian jump linear systems with state resets,” SIAM Journal on Control and Optimization, vol. 52, pp. 1809-1831, 2014. [ DOI | arXiv | http ]
[3]	M. Ogura and C. F. Martin, “Generalized joint spectral radius and stability of switching systems,” Linear Algebra and its Applications, vol. 439, no. 8, pp. 2222-2239, 2013. [ DOI | http ]
[2]	M. Ogura and Y. Yamamoto, “Dissipativity of pseudorational behaviors,” IEEE Transactions on Automatic Control, vol. 58, no. 4, pp. 823-833, 2013. [ DOI | http ]
[1]	M. Nagahara, M. Ogura, and Y. Yamamoto, “H∞ design of periodically nonuniform interpolation and decimation for non-band-limited signals,” SICE Journal of Control, Measurement, and System Integration, vol. 4, no. 5, pp. 341-348, 2011. 2012 SICE Best Paper Award. [ DOI | http ]

会议论文集

[63]	W. Imahayashi, T. Tokugawa, K. Koitabashi, Y. Tsunoda, M. Ogura, and S. Muto, “Actual experiment using mobile robot in sheepdog system -guidance route design using traveling salesman problem-,” in SICE Festival 2024 with Annual Conference (accepted), 2024.
[62]	J. Aizawa, M. Ogura, M. Shimono, and N. Wakamiya, “Manipulation of neuronal network firing patterns using temporal deep unfolding-based MPC,” in 2023 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2023, pp. 15-21. [ DOI | arXiv | http ]
[61]	Y. Deng, A. Li, M. Ogura, and N. Wakamiya, “Collision-free shepherding control of a single target within a swarm,” in 2023 IEEE International Conference on Systems, Man, and Cybernetics, 2023, pp. 5218-5223. [ DOI | arXiv | http ]
[60]	A. Fujioka, M. Ogura, and N. Wakamiya, “Proposal and evaluation of pursuit formations based on cyclic pursuit dynamics,” in 2023 International Symposium on Nonlinear Theory and its Applications, 2023, pp. 30-33. [ DOI | http ]
[59]	M. Ogura and V. M. Preciado, “Asynchronous temporal interactions promote disparity in networks,” in 2023 International Symposium on Nonlinear Theory and its Applications, 2023, p. 25. [ DOI | http ]
[58]	C. Zhao, X. Gong, Y. Ebihara, and M. Ogura, “Impulse-to-peak optimization of positive linear systems via DC programming,” in 22nd IFAC World Congress, 2023, pp. 5544-5549. [ DOI | http ]
[57]	A. Fujioka, M. Ogura, and N. Wakamiya, “Shepherding heterogeneous flocks: overview and prospect,” in 22nd IFAC World Congress, 2023, pp. 11523-11526. [ arXiv ]
[56]	Y. Deng, A. Li, M. Ogura, and N. Wakamiya, “Collision-free property analysis for the shepherding swarm,” in SICE Annual Conference 2023, 2023, pp. 1072-1073.
[55]	J. Aizawa, M. Ogura, M. Shimono, and N. Wakamiya, “Temporal deep unfolding-based MPC for controlling firing patterns of neuronal network,” in 2023 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, 2023.
[54]	A. Li, M. Ogura, and N. Wakamiya, “Proposal of a bearing-only shepherding algorithm with limited sensing capabilities,” in AROB-ISBC-SWARM 2023, 2023, pp. GS34-1.
[53]	Y. Deng, M. Ogura, A. Li, and N. Wakamiya, “Shepherding control for separating a single agent from a swarm,” in 1st IFAC Workshop on Control of Complex Systems, 2022, pp. 217-222. [ DOI | arXiv | http ]
[52]	A. Li, M. Ogura, Y. Tsunoda, and N. Wakamiya, “Proposal of farthest-agent targeting algorithm with indirect chasing,” in SICE Annual Conference 2022, 2022, pp. 92-94.
[51]	A. Fujioka, M. Ogura, and N. Wakamiya, “Shepherding algorithm based on variant agent detection for heterogeneous flock,” in SICE Annual Conference 2022, 2022, pp. 87-91. Finalists of SICE Annual Conference 2022 Young Author's Award. [ DOI | http ]
[50]	M. Ogura, K. Kobayashi, and K. Sugimoto, “Static output feedback synthesis of time-delay linear systems via deep unfolding,” in 17th IFAC Workshop on Time Delay Systems, 2022, pp. 214-215. [ arXiv ]
[49]	M. Kishida and M. Ogura, “Temporal deep unfolding for nonlinear stochastic optimal control,” in 7th International Conference on Advances in Control & Optimization of Dynamical Systems, 2022, pp. 908-913. [ DOI | http ]
[48]	M. Ogura and N. Wakamiya, “Model predictive control of fish schooling model with reduced-order prediction model,” in 60th IEEE Conference on Decision and Control, 2021, pp. 4115-4120. [ DOI | http ]
[47]	M. Kishida and M. Ogura, “Temporal deep unfolding for nonlinear maximum hands-off control,” in SICE Annual Conference 2021, 2021, pp. 1007-1010. [ arXiv ]
[46]	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. 33-39. [ DOI | arXiv | http ]
[45]	M. Kumazaki, M. Ogura, and T. Tachibana, “Service chain construction with efficient VNF sharing based on model predictive control,” in 2020 International Conference on Emerging Technologies for Communications, 2020, pp. M1-5. [ DOI | http ]
[44]	K. Sugimoto, M. Ogura, K. Hanada, and T. Aihara, “Sampled-data suboptimal state estimation over lossy networks,” in 52nd ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 2020, pp. 79-83. [ DOI | http ]
[43]	C. Zhao, M. Ogura, and K. Sugimoto, “Finite-time control of discrete-time positive linear systems via convex optimization,” in SICE Annual Conference 2020, 2020, pp. 1230-1235. [ DOI | arXiv | http ]
[42]	T. Kimura and M. Ogura, “Distributed collaborative 3D-deployment of UAV base stations for on-demand coverage,” in IEEE International Conference on Computer Communications 2020, 2020, pp. 1748-1757. Acceptance rate 19.8 percent. [ DOI | arXiv | http ]
[41]	Y. Abe, M. Ogura, H. Tsuji, A. Miura, and S. Adachi, “Resource and network management for satellite communications systems: a chance-constrained approach,” in 21st IFAC World Congress, 2020, pp. 3304-3309. [ DOI | http ]
[40]	M. Aida, C. Takano, and M. Ogura, “On the fundamental equation of user dynamics and the structure of online social networks,” in NetSci-X 2020, 2020, pp. 155-170. [ DOI | arXiv | http ]
[39]	M. Ogura, W. Mei, and K. Sugimoto, “Upper-bounding dynamics on networked synergistic susceptible-infected-susceptible model,” in SICE Annual Conference 2019, 2019, pp. 1430-1431.
[38]	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. [ DOI | http ]
[37]	M. Ogura, M. Kishida, K. Hayashi, and J. Lam, “Geometric programming for optimizing stability of distributed power control algorithms,” in SICE Annual Conference 2019, 2019, pp. 679-680.
[36]	M. Ogura, M. Kishida, K. Hayashi, and J. Lam, “Resource allocation for robust stabilization of Foschini-Miljanic Algorithm,” in 2019 American Control Conference, 2019, pp. 4030-4035. [ DOI | http ]
[35]	M. Kumazaki, M. Ogura, and T. Tachibana, “VNF management with model predictive control for multiple service chains,” in IEEE International Conference on Consumer Electronics - Taiwan, 2019. [ http ]
[34]	T. Tadenuma, M. Ogura, and K. Sugimoto, “Sampled-data state observation over lossy networks under round-robin scheduling,” in 5th IFAC Conference on Analysis and Control of Chaotic Systems, 2018, pp. 197-202. Young Author Award Finalist. [ DOI | arXiv | http ]
[33]	W. Mei and M. Ogura, “Instability analysis of Markov jump linear systems by spectral optimization,” in SICE Annual Conference 2018, 2018, pp. 419-422.
[32]	M. Ogura, J. Wan, and S. Kasahara, “Model predictive control for energy-efficient operation of data centers with cold aisle containments,” in 6th IFAC Conference on Nonlinear Model Predictive Control, 2018, pp. 241-246. [ DOI | arXiv | http ]
[31]	M. Ogura and J. Harada, “Resource allocation for containing epidemics from temporal network data,” in 23rd International Symposium on Mathematical Theory of Networks and Systems, 2018, pp. 537-542. [ arXiv | .pdf ]
[30]	M. Ogura, J. Tagawa, and N. Masuda, “Distributed agreement on activity driven networks,” in 2018 American Control Conference, 2018, pp. 4147-4152. [ DOI | arXiv | http ]
[29]	X. Chen, M. Ogura, K. R. Ghusinga, A. Singh, and V. M. Preciado, “Semidefinite bounds for moment dynamics: Application to epidemics on networks,” in 56th IEEE Conference on Decision and Control, 2017, pp. 2448-2454. [ DOI | http ]
[28]	M. Wakaiki, M. Ogura, and J. P. Hespanha, “Linear quadratic control for sampled-data systems with stochastic delays,” in 2017 American Control Conference, 2017, pp. 1978-1983. [ DOI | http ]
[27]	M. Ogura and V. M. Preciado, “Katz centrality of Markovian temporal networks: analysis and optimization,” in 2017 American Control Conference, 2017, pp. 5001-5006. [ DOI | arXiv ]
[26]	M. Ogura and V. M. Preciado, “Efficient containment of exact SIR Markovian processes on networks,” in 55th IEEE Conference on Decision and Control, 2016, pp. 967-972. 平成29年度計測自動制御学会関西支部支部長賞奨励賞. [ DOI | arXiv ]
[25]	M. Ogura, M. Wakaiki, and V. M. Preciado, “Dynamic analysis of bet-hedging strategies as a protection mechanism against environmental fluctuations,” in 55th IEEE Conference on Decision and Control, 2016, pp. 4178-4183. [ DOI | arXiv ]
[24]	M. Wakaiki, M. Ogura, and J. P. Hespanha, “Robust stability under asynchronous sensing and control,” in 55th IEEE Conference on Decision and Control, 2016, pp. 5962-5967. [ DOI | http ]
[23]	M. Ogura, A. Cetinkaya, T. Hayakawa, and V. M. Preciado, “Efficient criteria for stability of large-scale networked control systems,” in 6th IFAC Workshop on Distributed Estimation and Control in Networked Systems, 2016, pp. 13-18. [ DOI | http ]
[22]	V. M. Preciado and M. Ogura, “Structural analysis of spreading processes from ego-nets,” in 6th IFAC Workshop on Distributed Estimation and Control in Networked Systems, 2016, pp. 345-350. [ DOI | http ]
[21]	M. Ogura, M. Wakaiki, J. P. Hespanha, and V. M. Preciado, “L2-gain analysis of regenerative switched linear systems under sampled-data state-feedback control,” in 2016 American Control Conference, 2016, pp. 709-714. [ DOI | http ]
[20]	M. Ogura and V. M. Preciado, “Optimal design of networks of positive linear systems under stochastic uncertainty,” in 2016 American Control Conference, 2016, pp. 2930-2935. [ DOI | arXiv | http ]
[19]	M. Ogura and V. M. Preciado, “Spreading processes over socio-technical networks with phase-type transmissions,” in 54th IEEE Conference on Decision and Control, 2015, pp. 3548-3553. [ DOI | arXiv | http ]
[18]	M. Ogura and V. M. Preciado, “Cost-optimal switching protection strategy in adaptive networks,” in 54th IEEE Conference on Decision and Control, 2015, pp. 3574-3579. [ DOI | arXiv | http ]
[17]	C. Nowzari, M. Ogura, V. M. Preciado, and G. J. Pappas, “A general class of spreading processes with non-Markovian dynamics,” in 54th IEEE Conference on Decision and Control, 2015, pp. 5073-5078. [ DOI | arXiv | http ]
[16]	M. Ogura, M. Nagahara, and V. M. Preciado, “L1-optimal disturbance rejection for disease spread over time-varying networks,” in SWARM 2015: The First International Symposium on Swarm Behavior and Bio-Inspired Robotics, 2015, pp. 377-378.
[15]	C. Nowzari, M. Ogura, V. M. Preciado, and G. J. Pappas, “Optimal resource allocation for containing epidemics on time-varying networks,” in 49th Asilomar Conference on Signals, Systems and Computers, 2015, pp. 1333-1337. [ DOI | http ]
[14]	M. Ogura and V. M. Preciado, “Disease spread over randomly switched large-scale networks,” in 2015 American Control Conference, 2015, pp. 1782-1787. [ DOI | arXiv | http ]
[13]	M. Ogura, A. Cetinkaya, and V. M. Preciado, “State-feedback stabilization of Markov jump linear systems with randomly observed Markov states,” in 2015 American Control Conference, 2015, pp. 1764-1769. [ DOI | arXiv | http ]
[12]	M. Ogura and R. M. Jungers, “Efficiently computable lower bounds for the p-radius of switching linear systems,” in 53rd IEEE Conference on Decision and Control, 2014, pp. 5463-5468. [ DOI | http ]
[11]	M. Ogura and C. F. Martin, “Mean stability of continuous-time semi-Markov jump linear positive systems,” in 2014 American Control Conference, 2014, pp. 3261-3266. [ DOI | http ]
[10]	M. Ogura and C. F. Martin, “On the mean stability of a class of switched linear systems,” in 52nd IEEE Conference on Decision and Control, 2013, pp. 97-102. [ arXiv | http ]
[9]	M. Ogura and C. F. Martin, “Stability of switching systems and generalized joint spectral radius,” in 2013 European Control Conference, 2013, pp. 3185-3190. [ DOI | http ]
[8]	M. Ogura and C. F. Martin, “Stochastic properties of switched Riccati differential equations,” in 51st IEEE Conference on Decision and Control, 2012, pp. 1319-1324. [ DOI | http ]
[7]	M. Ogura, Y. Yamamoto, and J. C. Willems, “On the dissipativity of pseudorational behaviors,” in 49th IEEE Conference on Decision and Control, 2010, pp. 1737-1742. [ DOI | http ]
[6]	Y. Yamamoto, J. C. Willems, and M. Ogura, “Pseudorational behaviors and Bezoutians,” in 19th International Symposium on Mathematical Theory of Networks and Systems, 2010, pp. 1917-1921.
[5]	M. Ogura and Y. Yamamoto, “Dissipativity of pseudorational behaviors,” in 19th International Symposium on Mathematical Theory of Networks and Systems, 2010, pp. 849-853.
[4]	M. Ogura and Y. Yamamoto, “Hankel norm computation for pseudorational transfer functions,” in 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, 2009, pp. 5502-5507. [ DOI | http ]
[3]	M. Nagahara, M. Ogura, and Y. Yamamoto, “A novel approach to repetitive control via sampled-data H∞ filters,” in 7th Asian Control Conference, 2009, pp. 160-165. [ http ]
[2]	M. Nagahara, M. Ogura, and Y. Yamamoto, “Interpolation of nonuniformly decimated signals via sampled-data H∞ optimization,” in SICE Annual Conference 2008, 2008, pp. 1151-1154. [ DOI | http ]
[1]	M. Ogura, M. Nagahara, and Y. Yamamoto, “Optimal wavelet expansion via sampled-data H∞ control theory,” in SICE Annual Conference 2007, 2007, pp. 1422-1426. [ DOI | http ]

学位论文

[3]	M. Ogura, “Mean Stability of Switched Linear Systems,” Ph.D. dissertation, Texas Tech University, 2014. [ http ]
[2]	M. Ogura, “Hankel Norm Computation for Pseudorational Transfer Functions (in Japanese),” Master's thesis, Kyoto University, 2009.
[1]	M. Ogura, “Optimal Wavelet Expansion via H∞ Sampled-Data Optimal Control Theory (in Japanese),” Bachelor report, Kyoto University, 2007.