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樊立萍, 高振博. 植物微生物燃料电池的自适应反步模糊控制及并网优化[J]. 太阳能学报, 2025,46(12):417-425.
樊立萍, 高振博. 植物微生物燃料电池的自适应反步模糊控制及并网优化[J]. 2025, 46(12): 417-425.
樊立萍, 高振博. 植物微生物燃料电池的自适应反步模糊控制及并网优化[J]. 太阳能学报, 2025,46(12):417-425. DOI: doi:10.19912/j.0254-0096.tynxb.2024-1430.
樊立萍, 高振博. 植物微生物燃料电池的自适应反步模糊控制及并网优化[J]. 2025, 46(12): 417-425. DOI: doi:10.19912/j.0254-0096.tynxb.2024-1430.
针对常规最大功率点跟踪算法(MPPT)在单室植物微生物燃料电池(SPMFC)控制中存在跟踪速度慢、局部最优等问题
结合自适应反步控制与模糊控制
提出一种混合算法
利用模糊控制器的逻辑推理能力克服非线性与耦合性对跟踪速度的影响
借助反步控制的自适应性和鲁棒性避免局部最优
并对SPMFC进行并网测试。结果表明:自适应反步-模糊控制使得SPMFC获得更大的输出功率和更快的跟踪速度
既实现对SPMFC最大功率点的无差跟踪
又能够保障并网后的电网对称
有效解决SPMFC产电功率低、MPPT出现局部最优及并网时网侧不对称等问题。
To address the issues of slow tracking speed and local optimum of conventional maximum power point tracking (MPPT) algorithms for single chamber plant microbial fuel cells (SPMFC)
a hybrid algorithm combining adaptive backstepping control and fuzzy control is proposed. This algorithm utilizes the logical reasoning capabilities of a fuzzy controller to overcome the effects of nonlinearity and coupling on tracking speed
and leverages the adaptability and robustness of backstepping control to avoid local optimum. Grid-connected tests are conducted on the SPMFC. The results indicate that the adaptive backstepping-fuzzy control enables the SPMFC to achieve higher output power and faster tracking speed
ensuring accurate tracking of the maximum power point and maintaining grid symmetry after grid connection. This effectively solves the issues of low power generation in SPMFCs
local optimum in MPPT
and asymmetry on the grid side during grid connection.
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樊立萍, 陈其鹏. 基于萤火虫优化模糊P&O的微生物燃料电池最大功率点跟踪[J]. 太阳能学报, 2024, 45(4): 373-381.
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