Li Mingyang’s research while affiliated with Jilin University and other places

In this paper, the novel adjacent two-end link or network multi-end link concept of software-defined network is presented to support the data transmission of electroencephalogram, audio and video streaming in spread spectrum communications. Instead of solving the problem of software-defined prioritization scheme in networking calculation and communication, the southbound-northbound structure of existing neural or information network is found in control and perceptual interactions. The proposed framework of multi-lead and multi-media structures allow the human-centric Metaverse to execute different operations for local and global planning schemes with the high-speed lead or media data transmission of spread spectrum streaming, depending on the kind of brain-computer interaction, and similar to the system of multi-modal perception in the routing or switching. Firstly, this research designed the filed programmable gate array for conventional routing nodes in the computation of different neural networks. Secondly, this study demonstrates its enhanced applicability with software core for multiple routers in the computing power network of the Internet of brains in different brain-computer smart terminals. Experiment results also show the benefits of proposed model and structure, and exposing the different running indicators in the simulation.

In order to solve the problems of high time complexity and insufficient global exploration ability of the battle royale optimization algorithm, this paper proposes an improved battle royale optimization algorithm based on chaos mapping, center selection and elite adaptive strategy. Through benchmark function testing, compared to particle swarm optimization algorithm, whale optimization algorithm, and the battle royale optimization algorithm, the improved algorithm significantly reduces time complexity and notably enhances convergence precision, speed, and stability. The improved algorithm is applied to the inverse kinematics problem of robots. The accuracy and The stability of the improved algorithm is better than those of the traditional battle royale optimization algorithm, it demonstrates superior solving precision and stability, proving its practicality and potential for development in solving robot inverse kinematics problems.

In order to study the thermal deformation behavior of uranium-50wt.%zirconium, used Gleeble 3800 thermal simulation testing machine to carry out compression deformation experiments at different temperatures for this material. The effects of deformation temperature and strain rate on the alloy were studied. The results show that the peak stress of U-50wt.%Zr metallic fuel decreases with the increase of deformation temperature after thermal deformation at 500°C~600°C, especially at 600°C compared with that at 500°C and 550°C. At the same temperature, the peak stress increases with the increase of strain rate, especially the peak stress at strain rate 0.1s-1 and 1s-1 is significantly higher than that at strain rate 0.01s-1, and then the microstructure and diffraction results of U-50wt.%Zr metal-type fuel after thermal deformation are compared and analyzed, and the Arrhenius-type constitutive equation and thermal proces550℃,έ=1s-1 diagram of U-50wt.%Zr metal-type fuel are established based on the peak stress.

Electric vehicles are being used on a large scale, and virtual power plants are redefining electric vehicles. A profit maximization model of EVs charging/discharging is constructed in this paper.The model is aimed at the maximum profits, while being constrained by power/energy storage batteries charging/discharging capacities and the travel needs of EVs.The model also express the charging/discharging decision of EVs very well. An analysis and calculation of the economic benefit and charging distribution of EV charging/discharging have been made by simulating user travel needs with Monte Carlo method. The data of the user travel rule come from NHTS (National Household Travel Survey) in 2021. The results indicate the rational charging/discharging model which can be significantly improved by responding to the TOU(Time Of Use) and RT (Real-Time) electricity price. Meanwhile, due to the cheaper off-peak electricity price at night, the expensive on-peak electricity price during the day, electric vehicles tend to charge at low load time and discharge at peak load time inversely so as to achieve peak load shifting. The power/energy storage batteries storage function of EVs is worth further developing.

This paper presents a novel fixed-time extended state observer-based control approach for forming and maintaining formations of multi-Unmanned Surface Vehicles (multi-USVs) in the presence of frequent ocean environmental disturbances and uncertain model parameters. Firstly, a simplified three-degree-of-freedom kinematic and dynamic model is established for the USVs. This model allows us to transform the formation control problem into a consensus control problem, aiming to achieve coherence among the formation errors within the system. Furthermore, a potential function is devised to address the issue of inter-vehicle collision avoidance, thereby significantly enhancing safety during both formation and maintenance processes. Moreover, a control strategy based on integral sliding mode is designed to minimize chattering phenomena in the control process. This ensures that the multi-USVs system can precisely establish and sustain the desired formation. Simultaneously, an improved fal-function-based fixed-time extended state observer is adopted to handle unknown disturbances caused by wind, waves, and currents during the formation maintenance. This enhanced observer not only accelerates convergence speed but also reduces the total estimation error compared to traditional observers. Finally, the Lyapunov stability is utilized to demonstrate the asymptotic stability of the entire control system.