Autor: |
Feifan Song, Yanpeng Zhou, Changxian Xu, Zhongbo Sun |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
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Zdroj: |
Frontiers in Neurorobotics, Vol 18 (2024) |
Druh dokumentu: |
article |
ISSN: |
1662-5218 |
DOI: |
10.3389/fnbot.2024.1446508 |
Popis: |
To reduce transportation time, a discrete zeroing neural network (DZNN) method is proposed to solve the shortest path planning problem with a single starting point and a single target point. The shortest path planning problem is reformulated as an optimization problem, and a discrete nonlinear function related to the energy function is established so that the lowest-energy state corresponds to the optimal path solution. Theoretical analyzes demonstrate that the discrete ZNN model (DZNNM) exhibits zero stability, effectiveness, and real-time performance in handling time-varying nonlinear optimization problems (TVNOPs). Simulations with various parameters confirm the efficiency and real-time performance of the developed DZNNM for TVNOPs, indicating its suitability and superiority for solving the shortest path planning problem in real time. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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