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20172023
most citedSelf-triggered Consensus of Multi-agent Systems with Quantized Relative State Measurements

7 citations · 11 across the 7 of their papers we have counts for

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6 papers · 1 filter

eess.SY2023★ 1 cited

Self-triggered Resilient Stabilization of Linear Systems with Quantized Output

Wenjie Liu, Masashi Wakaiki, Jian Sun +2

This paper studies the problem of stabilizing a self-triggered control system with quantized output. Employing a standard observer-based state feedback control law, a self-triggeri…

eess.SY2022★ 7 cited

Self-triggered Consensus of Multi-agent Systems with Quantized Relative State Measurements

Masashi Wakaiki

This paper addresses the consensus problem of first-order continuous-time multi-agent systems over undirected graphs. Each agent samples relative state measurements in a self-trigg…

eess.SY2021

Cell Zooming with Masked Data for Off-Grid Small Cell Networks: Distributed Optimization Approach

Masashi Wakaiki, Katsuya Suto, Izumi Masubuchi

Cell zooming has been becoming an essential enabler for off-grid small cell networks. Traditional models often utilize the numbers of active users in order to determine cell zoomin…

eess.SY2017

Stabilization of Networked Control Systems under DoS Attacks and Output Quantization

Masashi Wakaiki, Ahmet Cetinkaya, Hideaki Ishii

This paper addresses quantized output feedback stabilization under Denial-of-Service (DoS) attacks. First, assuming that the duration and frequency of DoS attacks are averagely bou…

eess.SY2017

Quantized output feedback stabilization by Luenberger observers

Masashi Wakaiki, Tadanao Zanma, Kang-Zhi Liu

We study a stabilization problem for systems with quantized output feedback. The state estimate from a Luenberger observer is used for control inputs and quantization centers. Firs…

eess.SY2017

Supervisory Control of Discrete-event Systems under Attacks

Masashi Wakaiki, Paulo Tabuada, Joao P. Hespanha

We consider a multi-adversary version of the supervisory control problem for discrete-event systems, in which an adversary corrupts the observations available to the supervisor. Th…