This paper presents a tiltable cable-suspended aerial manipulation (SAM) system designed to improve the utility of aerial manipulators in industrial settings. Although drone-robot arm systems have shown promise, suspended configurations encounter notable stability challenges, particularly during inclined operations. To tackle these challenges, we performed simulation-based analyses focusing on the system's kinematics, dynamic response, and thrust requirements under tilted conditions. We utilized Monte Carlo sampling and forward kinematics to assess the workspace and manipulability. The findings indicated that each propeller needs to generate over 32 N of thrust to maintain stable control. Additionally, simulation experiments showed that the system can uphold its attitude and execute end-effector motions effectively, even in the presence of disturbances. This study establishes a foundational verification step toward developing a physical SAM system capable of safe and robust operation in inclined scenarios.

It is important to minimize electric energy consumption of a data center that uses enormous electricity for maintaining an adequate indoor temperature. Most data centers have applied the outdoor air cooling method on account of economic feasibility. However, it is necessary that data centers have an efficient control method in order to achieve extra energy savings. In this paper, we propose an artificial intelligence based real-time optimal control method that minimizes electricity consumption and assures safe operation simultaneously. The main idea of our proposed method is to evolutionary search the optimal range of controlled variable during a normally operative condition. Furthermore, an optimal operating condition can be achieved without requiring large-scale data to learn a model. Experimental results demonstrate that indoor temperature of a data center can be constantly controlled safely and cost effectively based on our proposed methodology.