Výsledky vyhledávání - "Takai, Shigemasa"

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Synthesis of Event-triggered Controllers for SIRS Epidemic Models

Autor: Ding, Lichen, Hashimoto, Kazumune, Takai, Shigemasa

In this paper, we investigate the problem of mitigating epidemics by applying an event-triggered control strategy. We consider a susceptible-infected-removed-susceptible (SIRS) model, which builds upon the foundational SIR model by accounting for rei

Externí odkaz: http://arxiv.org/abs/2310.09480

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Bayesian Meta-Learning on Control Barrier Functions with Data from On-Board Sensors

Autor: Hashimoto, Wataru, Hashimoto, Kazumune, Wachi, Akifumi, Shen, Xun, Kishida, Masako, Takai, Shigemasa

In this paper, we consider a way to safely navigate the robots in unknown environments using measurement data from sensory devices. The control barrier function (CBF) is one of the promising approaches to encode safety requirements of the system and

Externí odkaz: http://arxiv.org/abs/2308.05306

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Neural Controller Synthesis for Signal Temporal Logic Specifications Using Encoder-Decoder Structured Networks

Autor: Hashimoto, Wataru, Hashimoto, Kazumune, Kishida, Masako, Takai, Shigemasa

In this paper, we propose a control synthesis method for signal temporal logic (STL) specifications with neural networks (NNs). Most of the previous works consider training a controller for only a given STL specification. These approaches, however, r

Externí odkaz: http://arxiv.org/abs/2212.05200

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A Lifting Approach to Learning-Based Self-Triggered Control with Gaussian Processes

Autor: Zhijun, Wang, Hashimoto, Kazumune, Hashimoto, Wataru, Takai, Shigemasa

This paper investigates the design of self-triggered control for networked control systems (NCS), where the dynamics of the plant is unknown apriori. To deal with the nature of the self-triggered control, in which state measurements are transmitted t

Externí odkaz: http://arxiv.org/abs/2202.10174

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Akademický článek

Novel hybrid arithmetic-equilibrium optimizer as robust tuner for power system stabilizer (PSS) parameters in interconnected electrical power system

Autor: Robandi, Imam, Prakasa, Mohamad Almas, Djalal, Muhammad Ruswandi, Takai, Shigemasa, Sari, Arimbi Kumala, Musti, Mochammad Adri Satria

Publikováno v: In e-Prime - Advances in Electrical Engineering, Electronics and Energy December 2024 10

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STL2vec: Signal Temporal Logic Embeddings for Control Synthesis With Recurrent Neural Networks

Autor: Hashimoto, Wataru, Hashimoto, Kazumune, Takai, Shigemasa

In this paper, a method for learning a recurrent neural network (RNN) controller that maximizes the robustness of signal temporal logic (STL) specifications is presented. In contrast to previous methods, we consider synthesizing the RNN controller fo

Externí odkaz: http://arxiv.org/abs/2109.04636

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