四轮独立驱动汽车自动轨迹跟踪+横向稳定性控制 CarSim与Simulink联合控制目标为对给定轨迹进行跟踪(不带轨迹规划)同

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ZIP 四轮独立驱动汽车自动轨迹.zip 大约有11个文件
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四轮独立驱动汽车自动轨迹跟踪+横向稳定性控制 CarSim与Simulink联合 控制目标为对给定轨迹进行跟踪(不带轨迹规划)同时进行横向稳定性控制 上层控制器为MPC控制器，输出为附加横摆力矩和方向盘转角,采用了二自由度车辆模型 MPC控制器采用代码编写，原理一目了然 将MPC问题转化为了二次规划方法求解 下层为基于优化控制的转矩分配 带有完整详细的推导文档 可通过该模型学习：★MPC控制★将MPC转化为二次规划的方法★轨迹跟踪控制★MATLAB中二次规划和非线性规划的命令使用方法 MATLAB版本为2018b CarSim版本为2018
<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/89766853/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/89766853/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">技术文章<span class="ff2">：</span>四轮独立驱动汽车自动轨迹跟踪<span class="ff3">+</span>横向稳定性控制<span class="ff3"> CarSim<span class="_ _0"> </span></span>与<span class="_ _1"> </span><span class="ff3">Simulink<span class="_ _0"> </span></span>联合</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">摘要<span class="ff2">：</span>本文介绍了一种基于<span class="_ _1"> </span><span class="ff3">CarSim<span class="_ _0"> </span></span>与<span class="_ _1"> </span><span class="ff3">Simulink<span class="_ _0"> </span></span>联合的四轮独立驱动汽车自动轨迹跟踪加横向稳定</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">性控制的解决方案<span class="ff4">。</span>本文以<span class="_ _1"> </span><span class="ff3">MPC<span class="_ _0"> </span></span>控制器为上层控制器<span class="ff2">，</span>通过代码编写实现附加横摆力矩和方向盘转角</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">的输出<span class="ff2">，</span>同时采用二自由度车辆模型进行控制<span class="ff4">。</span>该解决方案将<span class="_ _1"> </span><span class="ff3">MPC<span class="_ _0"> </span></span>问题转化为二次规划方法求解<span class="ff2">，</span>并</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">通过基于优化控制的转矩分配实现下层控制<span class="ff4">。</span>本文还提供了完整的推导文档<span class="ff2">，</span>供读者学习<span class="_ _1"> </span><span class="ff3">MPC<span class="_ _0"> </span></span>控制<span class="ff4">、</span></div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">将<span class="_ _1"> </span><span class="ff3">MPC<span class="_ _0"> </span></span>转化为二次规划的方法<span class="ff4">、</span>轨迹跟踪控制以及<span class="_ _1"> </span><span class="ff3">MATLAB<span class="_ _0"> </span></span>中二次规划和非线性规划的命令使用方法</div><div class="t m0 x1 h3 y7 ff4 fs0 fc0 sc0 ls0 ws0">。</div><div class="t m0 x1 h2 y8 ff3 fs0 fc0 sc0 ls0 ws0">1.<span class="_ _2"> </span><span class="ff1">引言</span></div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">自动驾驶技术的发展已经取得了巨大的突破<span class="ff2">，</span>为汽车行业带来了革命性的变化<span class="ff4">。</span>汽车的自动轨迹跟踪</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">与稳定性控制是实现自动驾驶的重要组成部分<span class="ff4">。</span>本文介绍了一种基于<span class="_ _1"> </span><span class="ff3">CarSim<span class="_ _0"> </span></span>与<span class="_ _1"> </span><span class="ff3">Simulink<span class="_ _0"> </span></span>联合的解</div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">决方案<span class="ff2">，</span>能够实现四轮独立驱动汽车的自动轨迹跟踪和横向稳定性控制<span class="ff4">。</span></div><div class="t m0 x1 h2 yc ff3 fs0 fc0 sc0 ls0 ws0">2.<span class="_ _2"> </span><span class="ff1">解决方案概述</span></div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">本文的解决方案采用了<span class="_ _1"> </span><span class="ff3">MPC<span class="ff2">（</span>Model Predictive Control<span class="ff2">）</span></span>控制器作为上层控制器<span class="ff2">，</span>通过代码编</div><div class="t m0 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">写实现附加横摆力矩和方向盘转角的输出<span class="ff4">。</span>同时<span class="ff2">，</span>采用了二自由度车辆模型进行控制<span class="ff2">，</span>以实现对给定</div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">轨迹的准确跟踪<span class="ff4">。</span>为了解决<span class="_ _1"> </span><span class="ff3">MPC<span class="_ _0"> </span></span>问题<span class="ff2">，</span>本文将其转化为二次规划方法进行求解<span class="ff4">。</span>在下层控制方面<span class="ff2">，</span>采</div><div class="t m0 x1 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">用基于优化控制的转矩分配<span class="ff2">，</span>以确保系统的稳定性和可靠性<span class="ff4">。</span></div><div class="t m0 x1 h2 y11 ff3 fs0 fc0 sc0 ls0 ws0">3.<span class="_ _2"> </span>MPC<span class="_ _0"> </span><span class="ff1">控制器设计</span></div><div class="t m0 x1 h2 y12 ff3 fs0 fc0 sc0 ls0 ws0">MPC<span class="_ _0"> </span><span class="ff1">控制器是一种基于模型的控制方法<span class="ff2">，</span>能够实现系统的轨迹跟踪和稳定性控制<span class="ff4">。</span>本文采用了代码编</span></div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">写的方式实现<span class="_ _1"> </span><span class="ff3">MPC<span class="_ _0"> </span></span>控制器<span class="ff2">，</span>以满足对附加横摆力矩和方向盘转角的输出要求<span class="ff4">。</span>通过对二自由度车辆模</div><div class="t m0 x1 h2 y14 ff1 fs0 fc0 sc0 ls0 ws0">型的建模和参数设定<span class="ff2">，</span>可以实现对给定轨迹的准确跟踪<span class="ff4">。</span></div><div class="t m0 x1 h2 y15 ff3 fs0 fc0 sc0 ls0 ws0">4.<span class="_ _2"> </span><span class="ff1">二次规划方法求解<span class="_ _1"> </span></span>MPC<span class="_ _0"> </span><span class="ff1">问题</span></div><div class="t m0 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">为了实现<span class="_ _1"> </span><span class="ff3">MPC<span class="_ _0"> </span></span>控制器的计算和求解<span class="ff2">，</span>本文将其转化为二次规划问题<span class="ff4">。</span>借助<span class="_ _1"> </span><span class="ff3">MATLAB<span class="_ _0"> </span></span>中的二次规划和非</div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">线性规划的命令<span class="ff2">，</span>能够方便地求解系统的最优控制策略<span class="ff4">。</span>通过基于优化控制的转矩分配<span class="ff2">，</span>系统能够在</div><div class="t m0 x1 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">满足轨迹跟踪和稳定性要求的前提下<span class="ff2">，</span>实现最佳的能量利用和驾驶舒适性<span class="ff4">。</span></div><div class="t m0 x1 h2 y19 ff3 fs0 fc0 sc0 ls0 ws0">5.<span class="_ _2"> </span>CarSim<span class="_ _0"> </span><span class="ff1">与<span class="_ _1"> </span></span>Simulink<span class="_ _0"> </span><span class="ff1">的联合应用</span></div><div class="t m0 x1 h2 y1a ff3 fs0 fc0 sc0 ls0 ws0">CarSim<span class="_ _0"> </span><span class="ff1">是一种专业的汽车仿真软件<span class="ff2">，</span>能够模拟车辆的动力学行为和驾驶特性<span class="ff4">。</span></span>Simulink<span class="_ _0"> </span><span class="ff1">是一种广</span></div><div class="t m0 x1 h2 y1b ff1 fs0 fc0 sc0 ls0 ws0">泛应用于控制系统设计和仿真的工具<span class="ff4">。</span>本文将<span class="_ _1"> </span><span class="ff3">CarSim<span class="_ _0"> </span></span>与<span class="_ _1"> </span><span class="ff3">Simulink<span class="_ _0"> </span></span>进行了联合应用<span class="ff2">，</span>实现了对四轮</div><div class="t m0 x1 h2 y1c ff1 fs0 fc0 sc0 ls0 ws0">独立驱动汽车的自动轨迹跟踪和横向稳定性控制<span class="ff4">。</span>通过<span class="_ _1"> </span><span class="ff3">CarSim<span class="_ _0"> </span></span>可以获取车辆的动力学参数和轨迹信</div><div class="t m0 x1 h2 y1d ff1 fs0 fc0 sc0 ls0 ws0">息<span class="ff2">，</span>并将其输入到<span class="_ _1"> </span><span class="ff3">Simulink<span class="_ _0"> </span></span>中进行控制计算和仿真<span class="ff4">。</span></div><div class="t m0 x1 h2 y1e ff3 fs0 fc0 sc0 ls0 ws0">6.<span class="_ _2"> </span><span class="ff1">结论</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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