基于PLL的SMO滑模观测器算法，永磁同步电机无传感器矢量控制，跟基于反正切的SMO做对比，可以有效消除转速的抖动

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ZIP 基于的滑模观测器.zip 大约有11个文件
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  4. 基于的滑模观测器算法在无传感器矢.doc 2.29KB
  5. 基于的滑模观测器算法在永磁同步.txt 2.06KB
  6. 基于的滑模观测器算法在永磁同步电机无.txt 1.87KB
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基于PLL的SMO滑模观测器算法，永磁同步电机无传感器矢量控制，跟基于反正切的SMO做对比，可以有效消除转速的抖动。
<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/90182747/2/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/90182747/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">基于<span class="_ _0"> </span><span class="ff2">PLL<span class="_ _1"> </span></span>的<span class="_ _0"> </span><span class="ff2">SMO<span class="_ _1"> </span></span>滑模观测器算法在无传感器矢量控制中的应用</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">引言<span class="ff3">：</span></div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">随着信息技术的快速进步<span class="ff3">，</span>无传感器矢量控制成为了现代电机控制领域的一项重要技术<span class="ff4">。</span>在无传感器</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">矢量控制中<span class="ff3">，</span>精确估计电机转速对于实现准确控制至关重要<span class="ff4">。</span></div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">传统的无传感器矢量控制方法中使用的滑模观测器<span class="ff3">（<span class="ff2">Sliding Mode Observer</span>，<span class="ff2">SMO</span>）</span>算法能够有</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">效地估计电机转速<span class="ff3">，</span>但在实际应用中存在转速抖动的问题<span class="ff4">。</span>为了解决这个问题<span class="ff3">，</span>本文提出了一种基于</div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">相位锁定环路<span class="ff3">（<span class="ff2">Phase-Locked Loop</span>，<span class="ff2">PLL</span>）</span>的<span class="_ _0"> </span><span class="ff2">SMO<span class="_ _1"> </span></span>滑模观测器算法<span class="ff3">，</span>该算法能够显著降低转速抖</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">动<span class="ff3">，</span>提高系统控制性能<span class="ff4">。</span></div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">一<span class="ff4">、<span class="ff2">SMO<span class="_ _1"> </span></span></span>滑模观测器算法原理</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">滑模观测器是一种基于滑模理论的估计算法<span class="ff3">，</span>在无传感器矢量控制中被广泛应用<span class="ff4">。</span>其原理是通过引入</div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">滑模面<span class="ff3">，</span>在滑模面上实时观测电机状态并估计转速<span class="ff4">。</span></div><div class="t m0 x1 h2 yc ff1 fs0 fc0 sc0 ls0 ws0">基于<span class="_ _0"> </span><span class="ff2">SMO<span class="_ _1"> </span></span>的估计算法可用于无传感器矢量控制中<span class="ff3">，</span>但在实际应用中<span class="ff3">，</span>由于环境噪声和参数摄动的存在</div><div class="t m0 x1 h2 yd ff3 fs0 fc0 sc0 ls0 ws0">，<span class="ff1">传统的<span class="_ _0"> </span><span class="ff2">SMO<span class="_ _1"> </span></span>算法存在转速抖动的问题<span class="ff4">。</span>为了解决这个问题</span>，<span class="ff1">本文提出了一种基于<span class="_ _0"> </span><span class="ff2">PLL<span class="_ _1"> </span></span>的<span class="_ _0"> </span><span class="ff2">SMO<span class="_ _1"> </span></span>滑模</span></div><div class="t m0 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">观测器算法<span class="ff4">。</span></div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">二<span class="ff4">、</span>基于<span class="_ _0"> </span><span class="ff2">PLL<span class="_ _1"> </span></span>的<span class="_ _0"> </span><span class="ff2">SMO<span class="_ _1"> </span></span>滑模观测器算法设计</div><div class="t m0 x1 h2 y10 ff2 fs0 fc0 sc0 ls0 ws0">1.<span class="_ _2"> </span>PLL<span class="_ _1"> </span><span class="ff1">原理</span></div><div class="t m0 x1 h2 y11 ff2 fs0 fc0 sc0 ls0 ws0">PLL<span class="_ _1"> </span><span class="ff1">是一种常用的控制系统技术<span class="ff3">，</span>在通信和电力电子等领域有广泛应用<span class="ff4">。</span>其主要原理是通过将参考信</span></div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">号与系统输出信号进行比较<span class="ff3">，</span>调整控制参数来实现精确的锁相跟踪<span class="ff4">。</span></div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">在基于<span class="_ _0"> </span><span class="ff2">PLL<span class="_ _1"> </span></span>的<span class="_ _0"> </span><span class="ff2">SMO<span class="_ _1"> </span></span>滑模观测器算法中<span class="ff3">，</span>我们利用<span class="_ _0"> </span><span class="ff2">PLL<span class="_ _1"> </span></span>的相位锁定环路来对电机转速进行估计<span class="ff4">。</span>通过</div><div class="t m0 x1 h2 y14 ff1 fs0 fc0 sc0 ls0 ws0">将锁相环路的参考信号与滑模观测器输出的估计值进行比较<span class="ff3">，</span>我们可以实时调整<span class="_ _0"> </span><span class="ff2">PLL<span class="_ _1"> </span></span>的参数<span class="ff3">，</span>使得估</div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">计值与实际值更加接近<span class="ff3">，</span>从而减小转速抖动<span class="ff4">。</span></div><div class="t m0 x1 h2 y16 ff2 fs0 fc0 sc0 ls0 ws0">2.<span class="_ _2"> </span>SMO<span class="_ _1"> </span><span class="ff1">滑模观测器算法设计</span></div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">基于<span class="_ _0"> </span><span class="ff2">PLL<span class="_ _1"> </span></span>的<span class="_ _0"> </span><span class="ff2">SMO<span class="_ _1"> </span></span>滑模观测器算法主要包括以下几个步骤<span class="ff3">：</span></div><div class="t m0 x1 h2 y18 ff3 fs0 fc0 sc0 ls0 ws0">（<span class="ff2">1</span>）<span class="ff1">滑模面设计</span>：<span class="ff1">根据电机的动态特性和系统要求</span>，<span class="ff1">设计适当的滑模面</span>，<span class="ff1">以实现对电机状态的观测</span></div><div class="t m0 x1 h3 y19 ff4 fs0 fc0 sc0 ls0 ws0">。</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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