An Efficient Variable Step Solar Maximum Power Point Tracking Algorithm

Meng, Yang; Chen, Zunliang; Cheng, Hui; Wang, Enpu; Tan, Baohua

doi:10.3390/en16031299

Cited by 7 publications

(3 citation statements)

References 31 publications

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“…As noted by the authors of (Meng et al, 2023), Kalman filtering is an optimal recursive numerical computing algorithm characterized by the efficiency of program memory use, speed, and suitability for real-time data processing programs.…”

Section: Methodsmentioning

confidence: 99%

Implementation and analysis of a parallel kalman filter algorithm for lidar localization based on CUDA technology

Mochurad

2024

Front. Robot. AI

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Introduction: Navigation satellite systems can fail to work or work incorrectly in a number of conditions: signal shadowing, electromagnetic interference, atmospheric conditions, and technical problems. All of these factors can significantly affect the localization accuracy of autonomous driving systems. This emphasizes the need for other localization technologies, such as Lidar.Methods: The use of the Kalman filter in combination with Lidar can be very effective in various applications due to the synergy of their capabilities. The Kalman filter can improve the accuracy of lidar measurements by taking into account the noise and inaccuracies present in the measurements.Results: In this paper, we propose a parallel Kalman algorithm in three-dimensional space to speed up the computational speed of Lidar localization. At the same time, the initial localization accuracy of the latter is preserved. A distinctive feature of the proposed approach is that the Kalman localization algorithm itself is parallelized, rather than the process of building a map for navigation. The proposed algorithm allows us to obtain the result 3.8 times faster without compromising the localization accuracy, which was 3% for both cases, making it effective for real-time decision-making.Discussion: The reliability of this result is confirmed by a preliminary theoretical estimate of the acceleration rate based on Ambdahl’s law. Accelerating the Kalman filter with CUDA for Lidar localization can be of significant practical value, especially in real-time and in conditions where large amounts of data from Lidar sensors need to be processed.

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Section: Methodsmentioning

confidence: 99%

Implementation and analysis of a parallel kalman filter algorithm for lidar localization based on CUDA technology

Mochurad

2024

Front. Robot. AI

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“…Therefore, to support design reusability and system scalability, mesh networks are the most widely used topology in on-chip networks. (14) Wi-Fi modules typically operate in two modes, AP and Station. In the AP mode, the node generates a LAN that allows other devices to access and thus interact with data.…”

Section: Network Frameworkmentioning

confidence: 99%

Wireless Mesh Network and Its Application in Sports Agility Tests

Tan¹,

Cao²,

Wang³

et al. 2023

Sensors and Materials

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In view of the backward traditional training methods and the shortage of training funds in college sports, an agility training system based on a wireless mesh network is developed and evaluated. The network structure, initialization, and root node selection of the mesh network are described in detail. In the mesh network training scenario, the network topology is examined, and the response time and packet loss rate of the mesh network nodes are tested to demonstrate that the ad hoc network can transmit real-time data within the response time. The experimental data show that when the number of hops is n ≤ 2 and the response time of the mesh network nodes is less than 300 ms, the packet loss rate is 0%. The wireless mesh network solves the problem that the traditional Wi-Fi network is limited by the communication distance. It also allows more lower-level computer nodes to access the network and expands the training coverage.

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“… Wu (2015) researched an agile training instrument based on ZigBee technology, which cannot be networked between devices, and the training range is relatively limited. The training and testing methods for sensitive quality in relevant previous studies are relatively single, taking badminton as an example, there is a lack of research on sensitive quality in training special sports ( Meng, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Research on the development and testing methods of physical education and agility training equipment in universities

et al. 2023

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IntroductionBecause of the problems of insufficient funds and traditional training methods in college sports agile training, an agile training system based on a wireless ad hoc network was developed to evaluate the effect of improving the sensitive quality of ordinary college students. Based on the ESP-MESH network, the lower computer realizes automatic networking between devices and tests the performance of the mesh network. Fourteen male college students received 9 weeks of agility training, with seven students in each of two groups: traditional agility training and agile equipment training. The researchers evaluated the performance of both groups in rapid disguise, body coordination, changing movements, and predictive decision-making.ResultsThere was no significant difference between the groups before training, but there were significant differences in the four abilities after training (p < 0.01). The experimental group had significant differences in rapid direction change and physical coordination (p < 0.05), and in changing movement and predictive decision-making ability (p < 0.01).ConclusionBoth traditional training and agile equipment training improve the agility quality of college students, and the latter shows better results in certain abilities. However, limited by other physical qualities, the improvement of motor changes and predictive decision-making ability is not as obvious as the other two abilities.

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An Efficient Variable Step Solar Maximum Power Point Tracking Algorithm

Cited by 7 publications

References 31 publications

Implementation and analysis of a parallel kalman filter algorithm for lidar localization based on CUDA technology

Implementation and analysis of a parallel kalman filter algorithm for lidar localization based on CUDA technology

Wireless Mesh Network and Its Application in Sports Agility Tests

Research on the development and testing methods of physical education and agility training equipment in universities

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