Method for Maximum Power Control of Direct-drive Wave Power Device Based on Fuzzy Sliding Mode Control
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摘要: 海洋波浪能是一种新型清洁能源, 为提高直驱式波浪发电系统的发电功率和波浪能转换效率, 针对目前普遍使用的比例-积分-微分(PID)控制方法存在输出纹波较大、系统稳定性较差的问题, 提出基于模糊滑模控制的最大功率控制方法, 根据运行状态实时调整趋近律参数, 在实现最大功率跟踪的同时削弱输出纹波, 减小跟踪误差, 提高系统控制品质。文中以永磁直线发电机(PMLG)作为发电装置, 建立系统动力学模型, 并通过快速傅里叶变换方法预估不规则波浪主频, 设计满足最大功率策略的期望电流跟踪曲线; 在此基础上, 将常规PID、滑模控制方法与所提出的模糊滑模最大功率控制方法进行仿真对比, 结果表明: 模糊滑模控制方法在功率上有所提升且具有更好的准确性和稳定性。Abstract: Marine wave energy is a new type of clean energy. In order to improve the generation power and wave energy conversion efficiency of the direct-drive wave power generation system, a maximum power control method based on fuzzy sliding mode control was proposed. The method aimed at solving the problems of large output ripple and poor system stability of the commonly used proportional-integral-derivative(PID) control method. In addition, the reaching law parameters were adjusted in real time according to the running state. At the same time, while realizing maximum power tracking, the output ripple was weakened; the tracking error was reduced, and the control quality of the system was improved. In this paper, the permanent magnet linear generator was used as the power generation device, and a system dynamics model was established. The main frequency of irregular waves was estimated by fast Fourier transform (FFT), and the expected current tracking curve was designed to meet the maximum power strategy. On this basis, the conventional PID and sliding mode control methods were compared with the proposed fuzzy sliding mode maximum power control method. The results show that the fuzzy sliding mode control method has improved power and shown better accuracy and stability.
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图 4
$ {{\boldsymbol{s}}}_{{\boldsymbol{n}}} $ 和$ \mathop {{{\boldsymbol{s}}_{\boldsymbol{n}}}}\limits^{\;.} $ 隶属函数Figure 4. Membership function of
$ {\boldsymbol{s}}_{\boldsymbol{n}} $ and$ \mathop {{{\boldsymbol{s}}_{\boldsymbol{n}}}}\limits^{\;.} $ 
图 5
${\boldsymbol{ \Delta \varepsilon}} $ 隶属函数Figure 5. Membership function of
${\boldsymbol{ \Delta }}{\boldsymbol{\varepsilon}} $ 
图 7 PID控制下q轴跟踪电流及跟踪误差
Figure 7. Tracking current and tracking error at q-axis under PID control
图 8 滑模控制下q轴跟踪电流及跟踪误差
Figure 8. Tracking current and tracking error at q-axis under sliding mode control
图 9 模糊滑模控制下q轴跟踪电流及跟踪误差
Figure 9. Tracking current and tracking error at q-axis under fuzzy sliding mode control
图 11 不同控制下规则波浪平均功率
Figure 11. Average power curves of regular waves under different controls
图 12 不规则波浪波形及FFT分析频谱
Figure 12. Irregular wave waveform and FFT analysis of the spectrum
图 13 不规则波浪波形及FFT分析波形对比
Figure 13. Comparison of irregular wave waveform and FFT analysis of the spectrum
图 14 不规则波浪激励力和300倍速度的波形
Figure 14. Irregular wave excitation force and 300 times the speed of the waveform
图 15 PID控制下q轴跟踪电流和误差
Figure 15. Tracking current and error at q-axis under PID control
图 16 滑模控制下q轴跟踪电流和误差
Figure 16. Tracking current and error at q-axis under sliding mode control
图 17 模糊滑模控制下q轴跟踪电流和误差
Figure 17. Tracking current and error at q-axis under fuzzy sliding mode control
表 1 输出
${\boldsymbol{ \Delta}} {\boldsymbol{\varepsilon}} $ 模糊规则表Table 1. Table of
$ {\boldsymbol{\Delta}} {{\boldsymbol{\varepsilon}} } $ fuzzy rule$ \mathop {{s_n}}\limits^{\;.} $ sn NB NM NS ZO PS PM PB NB PB PB PB PB NM NS ZO NM PB PB PB PM NS ZO PS NS PB PB PM PS ZO PS PM ZO PB PM PS ZO NS NM NB PS PM PS ZO NS NM NB NB PM PS ZO NS NM NB NB NB PB ZO NS NM NB NB NB NB 
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表 2 仿真参数设置
Table 2. Setting of simulation parameter
变量 取值 变量 取值 d轴定子电感$ {L}_{d} $ 0.0114 H 运动部件总质量M 100 kg q轴定子电感$ {L}_{q} $ 0.0114 H 附加质量m 50 kg 定子电阻r 1 Ω 阻尼系数$ {R}_{1} $ 210 极对数n 4 浮力系数$ {K}_{1} $ 61.5 极距$ \tau $ 0.05 m 激励力幅值$ {F}_{m} $ 300 N 永磁体磁链$ {\varphi }_{f} $ 0.52 Wb 波浪频率$ \omega $ 0.5 π
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