With the arrival of population aging, the number of disabled people has increased, and existing populations with physical impairments. The dining problem is one of the most important problems they must solve. The feeding robot system has been introduced into the auxiliary nursing scene to reduce the burden of nursing staff. Multiple types of feeding robots have been developed. However most existing feeding robot systems still suffer from issues related to insufficient intelligence and convenience, with limited attention to user intention. To address this issue, we propose a vision-based algorithm for the interaction between the robot and users. This method effectively identifies user intentions for dining, menu selection, and chewing dynamics during meals. It enables the robot to operate more intelligently by the user’s intention without additional wearable devices, significantly enhancing user comfort and convenience. We conducted a series of experiments on dining intentions, selection menu intentions, and chewing dynamics during meals. The experimental results show that the average recognition rate of users’ dining intention is 98%, and the average recognition rate of chewing dynamics is 86.53%. This contribution presents an interactive approach for individuals without mobility, enhancing the intelligence of the feeding robot. It holds promise for future applications in nursing scenarios.
The low inertia power systems with high proportional power electronic inverters cannot provide sufficient inertia to maintain system balance. The inverters based on virtual synchronous generators (VSG) can provide virtual inertia to the grid. However, when the damping effect is not significant, the rotor motion characteristics brought about by the VSG may cause low frequency power oscillations. To solve this problem, a low-frequency oscillation suppression method (AI-VSG) for low-inertia power systems based on auxiliary inertia is proposed in this paper. Firstly, a power frequency control model of the grid-connected inverter system is developed. Next, the response performance of VSG and AI-VSG is compared and theoretically verified. Finally, as shown in the Bode diagram, the proposed method significantly attenuates power oscillations and improves the inertial response, even in the presence of poor system damping. The simulation results validate the effectiveness of the proposed oscillation suppression method.
KEYWORDS: Control systems, Frequency response, Seaborgium, Frequency modulation, Mathematical modeling, Device simulation, Design and modelling, Tunable filters, Renewable energy
The continuous access of renewable energy and distributed generation threatens the frequency security of microgrid. The frequency regulation capability of microgrid is greatly reduced. To improve the frequency stability of the microgrid based on energy storage, it is very important to adopt an appropriate frequency regulation method, which needs further research. Firstly, the principle of the virtual synchronous generator (VSG) is described, and the virtual power frequency and the virtual excitation controller are introduced. Thereafter, in order to improve the shortcomings of the traditional droop control, the frequency response is introduced to improve the droop control. Finally, the frequency regulation methods based on VSG, droop control, and improved droop control are simulated and compared. The results show that the frequency response link effectively improves the system stability. Among the three frequency regulation methods, the VSG performs the best frequency regulation speed as well as stability.
KEYWORDS: Control systems, Systems modeling, Modal analysis, Californium, Signal attenuation, Rutherfordium, Resistance, Inductance, Simulink, Seaborgium
Virtual synchronous generators (VSG) technology can improve the inertial supportability of the new power system. However, its support characteristics are easily to cause low-frequency oscillation of the system, and there is a lack of corresponding mechanism analysis. Aiming at the problem of low-frequency oscillation in VSG grid-connected system, the small-signal model of VSG grid-connected system is established by state space method, and the influence of system parameters on low-frequency oscillation mode is identified by root locus method. The correctness of the conclusion is verified by Matlab / Simulink time-domain simulation. The results show that increasing the moment of inertia of VSG, the characteristic root of low-frequency oscillation mode moves to the right of the coordinate system, which is not conducive to the stability of the system. Increasing the damping coefficient and reducing the voltage level, the corresponding characteristic root moves to the left of the coordinate system, which is conducive to improving the stability of the lowfrequency oscillation mode of the system.
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