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Under the network environment, the traditional control method of underwater Robot path has the disadvantages of low control accuracy, large error, and inefficiency. This paper proposes a novel path control method for underwater Robots based on the NURBS (nonuniform rational B-spline, NURBS) curve fitting method, which utilizes a sensor or camera to detect the static and dynamic obstacles, establishes the kinematics model of underwater Robots, gets the target function of rob shortest path, and analyzes underwater Robot constraints. According to the basic fluid mechanics, the resistance of the underwater Robot is determined. The filter function is used to smooth the process, and the NURBS curve fitting method is applied to control the path of the underwater Robot. Experimental results show that the improved method that proved to be practical is superior to the traditional one in the aspect of control time and accuracy.

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The new area of education has progressively become where virtual reality interacts and integrates. The influence of credit management in the learning process is improved by digital twin technology. The next study paradigms of learning space will be the reconstruction of smart learning spaces based on digital twins. Hence, this paper, Digital Twin Approach (DTA), has been proposed to reconstruct the learning area and encourage the education revolution and a new learning community. In real-time manual interaction, the simulated twin will imitate diverse scenarios and create situations through AI decision-making and automatic twin implementation. The use of digital twin technology offers a new technology integration and development path to smart-university management in the investigation of the construction of smart university facilities. Thus, the experimental results show that the DTA technology can motivate students to study and boost learning when effectively utilized.

For the identification problem of closed-loop subspace model, we propose a zero space projection method based on the estimation of correlation function to fill the block Hankel matrix of identification model by combining the linear algebra with geometry. By using the same projection of related data in time offset set and LQ decomposition, the multiplication operation of projection is achieved and dynamics estimation of the unknown equipment system model is obtained. Consequently, we have solved the problem of biased estimation caused when the open-loop subspace identification algorithm is applied to the closed-loop identification. A simulation example is given to show the effectiveness of the proposed approach. In final, the practicability of the identification algorithm is verified by hardware test of UAV servo system in real environment.