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                  水下机器人航向/轨迹跟踪控制系统设计--滑模控制
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          <p>本文给出滑模控制在水下机器人运动控制方面的两个实例，主要参考JJE Slotine的著作<em>Applied Nonlinear Control</em>。</p>
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          <p>最近设计滑模控制器需要用MATLAB Simulink中的User-Defined Function，写好Function后编译报错。报错信息为： <figure class="highlight plain"><table><tr><td class="gutter"><pre><div class="line">1</div></pre></td><td class="code"><pre><div class="line">No supported compiler or SDK was found.</div></pre></td></tr></table></figure></p>
<p>在<a href="https://cn.mathworks.com/matlabcentral/answers/246135-is-matlab-compatible-with-mac-os-x-10-11-el-capitan">MathWorks论坛</a>上有这个问题的解决方案。大致就是去App Store上安装Xcode就可以了，然而我并不想安装臃肿的Xcode且我已经安装了Xcode command line tool。这篇文章将教你如何花式配置mex。<br />
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          <p>混吃混喝-&gt;坐吃等死的大四生活开始啦(｡･ω･｡)
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          <p>这篇文章基本上是SoPC的课程设计报告，要求是使用SoPC EDA实验板开发一个电子钟，使用OLED显示时间，并支持按键修改时间。本文包括SoPC系统硬件消抖器的开发，定时中断与硬件中断的实现等内容。最终实现效果如下图所示 <img src="https://ws1.sinaimg.cn/large/005WMcFzly1fhx8t3ke7ej32io1w07vj.jpg" alt="电子钟显示效果" />
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          <ul>
<li>这篇文章是现代控制理论课程设计的前半部分，主要研究了单自由度弹性关节系统的工程背景，动力学建模；控制系统方面包括状态方程建立，状态转移矩阵计算，零输入给定初值<code>MATLAB</code>与<code>Python Tkinter</code>模型仿真，状态方程与传递函数之间的转换，系统能观性和能控性的讨论。</li>
<li>单自由度弹性关节示意图如下： <img src="https://ws1.sinaimg.cn/large/005WMcFzly1ffn2m7gikuj30by06pq3b.jpg" alt="单自由度弹性关节" /></li>
</ul>
<p><em>P.S.</em> 这篇文章的原排版系统为<code>LaTeX</code>，在<a href="https://www.sharelatex.com/project/5915c87ed1d7c39a6d050f86">ShareLaTeX</a>上可以导出<code>PDF</code>格式的报告，同时<code>LaTeX Source</code>也开放了公共阅读权限。
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<p>Can machines think? –AM Turing</p>
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<ul>
<li>写在文前：最近在学机器学习的相关知识，由于相关文档和更新速度的关系选择了当前较为流行的<a href="https://keras.io/">Keras</a>，一个基于python的深度学习框架。学校正在进行一个基于深度学习/强化学习(reinforcement learning)控制水下滑翔机的项目，我学习了一下Keras，并做了一些练习。这篇文章将水下滑翔机作为问题背景介绍一下用Keras和Sequential模型处理回归问题。</li>
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          <p>这学期<strong>过程控制</strong>课介绍了热电偶的相关知识，相对于<strong>检测技术</strong>课程更偏向于热电偶的实际应用。这篇文章将会介绍热电偶的基本原理和使用方法，介绍如何使用K型热电偶的正向/反向公式，并用MATLAB绘制SEEBACK曲线。</p>
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          <p>在这篇文章里我用Python实现了一个简单的互补滤波器来做角度融合，实现姿态解算。用到的传感器是<a href="https://www.invensense.com/products/motion-tracking/6-axis/mpu-6050/">MPU-6050</a>，使用树莓派的I2C总线读取传感器的底层数据。</p>
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          <p>不知不觉一学期又过去了，简单回忆和总结一下这学期的收获吧。</p>
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<li>上篇文章讲到了用树莓派和openCV库来做简单的循迹，在这篇文章里我们将尝试用树莓派做一些更酷的事情。我们不希望给小车具体的规则(explicitly programmed)去做循迹，而是让它自己从已有的数据集(包括图像与转向角)学习如何循迹，没错这就是机器学习。</li>
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