基于两种坐标系的超螺旋滑模观测器的永磁同步电机pmsm无位置（速度）传感器控制模型支持dq旋转坐标系和静止坐标系建立smo引入二阶滑模超螺旋算法替代一阶滑模dq坐标系引入锁相环PLL估计转速及

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ZIP 基于两种坐标.zip 大约有11个文件
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  4. 基于两种坐标系的超螺旋滑模观测.txt 307B
  5. 基于两种坐标系的超螺旋滑模观测器在永磁同步电.txt 2.01KB
  6. 基于两种坐标系的超螺旋滑模观测器在永磁同步电机无位.txt 2.13KB
  7. 基于两种坐标系的超螺旋滑模观测器的永磁同步电机.doc 1.61KB
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  9. 基于两种坐标系的超螺旋滑模观测器的永磁同步电机.txt 2.25KB
  10. 基于两种坐标系的超螺旋滑模观测器的永磁同步电机无位.txt 1.43KB
  11. 基于超螺旋滑模观测器的永磁同步电机无位置速度传感器.txt 2.29KB

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基于两种坐标系的超螺旋滑模观测器的永磁同步电机pmsm无位置（速度）传感器控制模型 支持 dq旋转坐标系和静止坐标系建立smo 引入二阶滑模超螺旋算法替代一阶滑模 dq坐标系引入锁相环PLL估计转速及转子位置 有效削弱抖振 赠送超螺旋滑模搭建推导文档及相关参考资料 仿真模型
<link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/90184259/2/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/90184259/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">基于两种坐标系的超螺旋滑模观测器的永磁同步电机<span class="ff2">（<span class="ff3">PMSM</span>）</span>无位置<span class="ff2">（</span>速度<span class="ff2">）</span>传感器控制模型</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">摘要<span class="ff2">：</span>永磁同步电机<span class="ff2">（<span class="ff3">PMSM</span>）</span>是一种在工业和汽车领域中广泛应用的高性能电机<span class="ff4">。</span>传统的控制方法需</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">要外部的位置或速度传感器来提供反馈信息<span class="ff2">，</span>但这种传感器在设计<span class="ff4">、</span>安装和维护上都存在一定的局限</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">性<span class="ff4">。</span>为了解决这个问题<span class="ff2">，</span>本文提出了一种基于两种坐标系的超螺旋滑模观测器<span class="ff2">（<span class="ff3">SMO</span>）</span>来实现<span class="_ _0"> </span><span class="ff3">PMSM</span></div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">的无位置<span class="ff2">（</span>速度<span class="ff2">）</span>传感器控制<span class="ff4">。</span></div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">引言<span class="ff2">：</span></div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">永磁同步电机<span class="ff2">（<span class="ff3">PMSM</span>）</span>是一种先进的电机<span class="ff2">，</span>在工业和汽车领域中得到了广泛的应用<span class="ff4">。</span>传统的<span class="_ _0"> </span><span class="ff3">PMSM<span class="_ _1"> </span></span>控</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">制方法需要外部的位置或速度传感器来提供反馈信息<span class="ff2">，</span>以实现对电机的精确控制<span class="ff4">。</span>然而<span class="ff2">，</span>这种传感器</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">的使用不仅增加了成本和复杂性<span class="ff2">，</span>而且在一些特殊环境下难以实现<span class="ff4">。</span>因此<span class="ff2">，</span>寻找一种无位置<span class="ff2">（</span>速度<span class="ff2">）</span></div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">传感器的控制方法对于提高<span class="_ _0"> </span><span class="ff3">PMSM<span class="_ _1"> </span></span>的性能和降低成本具有重要意义<span class="ff4">。</span></div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">方法<span class="ff2">：</span></div><div class="t m0 x1 h2 yc ff1 fs0 fc0 sc0 ls0 ws0">本文提出了一种基于两种坐标系的超螺旋滑模观测器<span class="ff2">（<span class="ff3">SMO</span>）</span>来实现<span class="_ _0"> </span><span class="ff3">PMSM<span class="_ _1"> </span></span>的无位置<span class="ff2">（</span>速度<span class="ff2">）</span>传感器</div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">控制<span class="ff4">。</span>该方法使用<span class="_ _0"> </span><span class="ff3">dq<span class="_ _1"> </span></span>旋转坐标系和静止坐标系来建立<span class="_ _0"> </span><span class="ff3">SMO<span class="ff2">，</span></span>并引入二阶滑模超螺旋算法替代传统的</div><div class="t m0 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">一阶滑模<span class="ff4">。</span>同时<span class="ff2">，<span class="ff3">dq<span class="_ _1"> </span></span></span>坐标系引入锁相环<span class="ff2">（<span class="ff3">PLL</span>）</span>来估计转速及转子位置<span class="ff4">。</span>这种方法能够有效削弱电机</div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">的抖振<span class="ff2">，</span>并提供良好的控制性能<span class="ff4">。</span></div><div class="t m0 x1 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">结果<span class="ff2">：</span></div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">通过对<span class="_ _0"> </span><span class="ff3">PMSM<span class="_ _1"> </span></span>进行仿真模型的建立和参数调整<span class="ff2">，</span>本文验证了基于两种坐标系的超螺旋滑模观测器的无</div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">位置<span class="ff2">（</span>速度<span class="ff2">）</span>传感器控制方法的有效性和实用性<span class="ff4">。</span>仿真结果表明<span class="ff2">，</span>该方法能够实现精确的转速和位置</div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">控制<span class="ff2">，</span>并且具有较好的鲁棒性和鲁棒性<span class="ff4">。</span></div><div class="t m0 x1 h2 y14 ff1 fs0 fc0 sc0 ls0 ws0">结论<span class="ff2">：</span></div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">本文提出了一种基于两种坐标系的超螺旋滑模观测器的永磁同步电机无位置<span class="ff2">（</span>速度<span class="ff2">）</span>传感器控制模型</div><div class="t m0 x1 h2 y16 ff4 fs0 fc0 sc0 ls0 ws0">。<span class="ff1">该方法通过引入二阶滑模超螺旋算法和<span class="_ _0"> </span><span class="ff3">PLL<span class="_ _1"> </span></span>估计转速及转子位置来实现对<span class="_ _0"> </span><span class="ff3">PMSM<span class="_ _1"> </span></span>的精确控制</span>。<span class="ff1">仿真</span></div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">结果验证了该方法的有效性和实用性<span class="ff2">，</span>为实现<span class="_ _0"> </span><span class="ff3">PMSM<span class="_ _1"> </span></span>的无位置<span class="ff2">（</span>速度<span class="ff2">）</span>传感器控制提供了一种新的解</div><div class="t m0 x1 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">决方案<span class="ff4">。</span></div><div class="t m0 x1 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">关键词<span class="ff2">：</span>永磁同步电机<span class="ff2">；</span>超螺旋滑模观测器<span class="ff2">；</span>无位置<span class="ff2">（</span>速度<span class="ff2">）</span>传感器<span class="ff2">；<span class="ff3">dq<span class="_ _1"> </span></span></span>旋转坐标系<span class="ff2">；</span>静止坐标系<span class="ff2">；</span></div><div class="t m0 x1 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">锁相环<span class="ff2">；</span>控制模型<span class="ff2">；</span>仿真模型<span class="ff2">；</span>精确控制<span class="ff2">；</span>鲁棒性<span class="ff4">。</span></div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>
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