首页|基于DRFNN滑模的多功能柔性多状态开关控制方法

基于DRFNN滑模的多功能柔性多状态开关控制方法

扫码查看
原文链接
  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
为了解决经典控制理论在带有分布式电源的配电网应用中存在精度低和稳定性差的问题，本研究提出了一种基于柔性多状态开关（FMS）的控制方法。该方法基于改进的双环递归模糊神经网络（DRFNN）滑模，旨在稳定地实现多条馈线的功率交互，以及单相接地故障的自适应电弧抑制功能。首先，提出了一种改进的DRFNN滑模控制（SMC）方法，旨在克服经典SMC固有的抖振和瞬态超调问题，减少对控制系统精确数学模型的依赖。为了提高系统的鲁棒性，设计了一种DRFNN的自适应参数调整策略，利用其动态映射能力提高暂态补偿能力。此外，还开发了一种基于微积分滑模表面的准连续二阶滑模控制器，以提高电流跟踪精度和系统稳定性。利用李雅普诺夫定理验证了所提方法的稳定性和网络参数的收敛性。在MATLAB/Simulink中构建了带控制系统的三端口FMS仿真模型。仿真结果通过对比分析验证了所提控制策略的可行性和有效性。
Control method based on DRFNN sliding mode for multifunctional flexible multistate switch
To address the low accuracy and stability when applying classical control theory in distribution networks with distributed generation,a control method involving flexible multistate switches(FMSs)is proposed in this study.This approach is based on an improved double-loop recursive fuzzy neural network(DRFNN)sliding mode,which is intended to stably achieve multiterminal power interaction and adaptive arc suppression for single-phase ground faults.First,an improved DRFNN sliding mode control(SMC)method is proposed to overcome the chattering and transient overshoot inherent in the classical SMC and reduce the reliance on a precise mathematical model of the control system.To improve the robustness of the system,an adaptive parameter-adjustment strategy for the DRFNN is designed,where its dynamic mapping capabilities are leveraged to improve the transient compensation control.Additionally,a quasi-continuous second-order sliding mode controller with a calculus-driven sliding mode surface is developed to improve the current monitoring accuracy and enhance the system stability.The stability of the proposed method and the convergence of the network parameters are verified using the Lyapunov theorem.A simulation model of the three-port FMS with its control system is constructed in MATLAB/Simulink.The simulation result confirms the feasibility and effectiveness of the proposed control strategy based on a comparative analysis.

Distribution networksFlexible multistate switchGrounding fault arc suppressionDouble-loop recursive fuzzy neural networkQuasi-continuous second-order sliding mode

廖江华、高伟、杨艳、杨耿杰

展开 >

College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108,P.R.China

Faculty of Automation Huaiyin Institute of Technology,Huai'an 223003,P.R.China

配电网 柔性多状态开关 接地故障电弧抑制 双环递归模糊神经网络 准连续二阶滑模

Natural Science Foundation of Fujian,China

2021J01633

2024

10.1016/j.gloei.2024.04.007

全球能源互联网(英文)

全球能源互联网(英文)

CSTPCDEI
ISSN：2096-5117
年,卷(期)：2024.7(2)
  • 28