| 研究実績の概要 |
In fiscal year 2017, the goals have two folds. First goal is to formulate a model predictive control (MPC) in order to optimize real-time control operations of the HiCoCPS system for proposing an efficient evolutionary algorithm of multiple objective optimization. Second goal is to evaluate the proposed time delay model with the safe-to-process algorithm for the HiCoCPS system. In control perspective, the implementation of the model predictive control (MPC) is successfully derived, simulated and benchmarked with four different seasons by using new evolutionary algorithm pursues the optimization of a dynamic multiple objective function, i.e., settling time and energy consumption for the energy efficient thermal comfort control in cyber-physical home system. The MPC is extended with energy optimization algorithm and self-adaptive model with a comprehensive quantitative analysis. In communication perspective, the time delay model by taking advantage of the proposed double average (DA) based scheme is examined under the HiCoCPS system, which consist of a main controller and two sub-controllers. The proposed DA-based scheme can guarantee 100% of safe-to-process regardless of any average inter-arrival time of two arrival tasks.
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