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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/15395

Title: Efficient Evolutionary Algorithm of Multi-objective Optimization for High-Confidence Cyber-Physical Systems
Authors: Lim, Yuto
Authors(alternative): リム, 勇仁
Keywords: Cyber-Physical Systems
Real-time System
Internet of Things
Predictive Control
Smart Homes
Issue Date: 1-Jun-2018
Abstract: 本研究の目的は、制御則設計と実時間計算制約との間のギャップを大規模で分散し効率的かつリアルタイムに縮むための、高信頼なサイバー物理システム(HiCoCPS)の新しいモデルを提案することです。その成果は、スマートホームおよび他のCPSベースのアプリケーションにおけるHiCoCPSの3つのモデルを設計および提案することを含む。以下の結果も含む:(1)Satisfiability Module Theoriesに基づく新規リアルタイムスケジューリング方法論フレームワークとタスクモデル、(2)2つのsafe-to-processスキームを用いた時間遅れモデル、(3)モデル予測制御を用いた最適化モデル。:The goal of this project to propose a novel model of high-confidence cyber-physical systems (HiCoCPS) for bridging the gap between control law design and real-time computation constraints in a large-scale, distributed, efficient and real-time manner. The outcomes include designing and proposing three models, i.e., task model, time delay model, and optimization model for the HiCoCPS system in the smart home application and other CPS-based domain applications. In summary, the results are: (1) novel real-time scheduling methodology framework and its task models based on Satisfiability Module Theories; (2) time delay model with two safe-to-process schemes; and (3) optimization model with model predictive control.
Description: 基盤研究(C)(一般)
Language: eng
URI: http://hdl.handle.net/10119/15395
Appears in Collections:2017年度 (FY 2017)

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