MPC主动悬架在Carsim-Simulink联合仿真中的性能验证与应用研究,**Carsim-Simulink联合仿真：MPC主动悬架系统性能验证与优化**,Carsim-Simulink联合仿真M
资源内容介绍
MPC主动悬架在Carsim-Simulink联合仿真中的性能验证与应用研究,**Carsim-Simulink联合仿真：MPC主动悬架系统性能验证与优化**,Carsim-Simulink联合仿真MPC主动悬架MPC是一种根据模型预测的方式在有限时域内求解最优解的控制方法，MPC善于处理多约束和多目标优化问题，计算时依据自定义的变量权重大小书写代价函数，通过二次规划求解，实现最优的控制效果。通过Carsim-Simulink联合仿真验证MPC控制效果，Carsim具有更加真实的动力学模型，使仿真结果更加准确，路面使用C级路面进行仿真。模型预测控制算法在simulink中编写的mfunction代码，模型对比主 被动悬架如簧载质量加速度、侧倾角速度、俯仰角速度等变量以观察MPC控制器控制效果。matlab代码中包括画图代码，可以将悬架性能指标绘制出来。主要分为两种模型：1. 在Carsim中提前制定好的路面，此模型在carsim的3D Road中提前做好路面进行仿真。2. 在联合仿真时，使用制作的考虑轮胎之间的相关性和延迟性的四轮路面激励输入给车辆模型，这个模型可以替为自 <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/90372503/2/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/90372503/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">MPC<span class="_ _0"> </span><span class="ff2">主动悬架的<span class="_ _1"> </span></span>Carsim-Simulink<span class="_ _0"> </span><span class="ff2">联合仿真研究</span></div><div class="t m0 x1 h2 y2 ff2 fs0 fc0 sc0 ls0 ws0">一<span class="ff3">、</span>引言</div><div class="t m0 x1 h2 y3 ff2 fs0 fc0 sc0 ls0 ws0">随着汽车工业的快速发展<span class="ff4">，</span>车辆主动悬架系统的研究已成为提高汽车行驶性能和乘坐舒适性的重要手</div><div class="t m0 x1 h2 y4 ff2 fs0 fc0 sc0 ls0 ws0">段<span class="ff3">。</span>模型预测控制<span class="ff4">（<span class="ff1">MPC</span>）</span>作为一种先进的控制方法<span class="ff4">，</span>具有处理多约束和多目标优化问题的优势<span class="ff3">。</span>本</div><div class="t m0 x1 h2 y5 ff2 fs0 fc0 sc0 ls0 ws0">文旨在通过<span class="_ _1"> </span><span class="ff1">Carsim-Simulink<span class="_ _0"> </span></span>联合仿真<span class="ff4">，</span>验证<span class="_ _1"> </span><span class="ff1">MPC<span class="_ _0"> </span></span>主动悬架的控制效果<span class="ff4">，</span>并对比主被动悬架的性</div><div class="t m0 x1 h2 y6 ff2 fs0 fc0 sc0 ls0 ws0">能指标<span class="ff3">。</span></div><div class="t m0 x1 h2 y7 ff2 fs0 fc0 sc0 ls0 ws0">二<span class="ff3">、<span class="ff1">MPC<span class="_ _0"> </span></span></span>控制方法</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">MPC<span class="_ _0"> </span><span class="ff2">是一种基于模型预测的方法<span class="ff4">，</span>在有限时域内求解最优解<span class="ff3">。</span>其核心是根据当前状态和预测模型<span class="ff4">，</span>计</span></div><div class="t m0 x1 h2 y9 ff2 fs0 fc0 sc0 ls0 ws0">算出在未来一段时间内的最优控制序列<span class="ff3">。<span class="ff1">MPC<span class="_ _0"> </span></span></span>通过自定义的变量权重大小书写代价函数<span class="ff4">，</span>通过二次规</div><div class="t m0 x1 h2 ya ff2 fs0 fc0 sc0 ls0 ws0">划求解<span class="ff4">，</span>实现最优的控制效果<span class="ff3">。</span>由于<span class="_ _1"> </span><span class="ff1">MPC<span class="_ _0"> </span></span>可以处理多约束和多目标优化问题<span class="ff4">，</span>因此在主动悬架控制中</div><div class="t m0 x1 h2 yb ff2 fs0 fc0 sc0 ls0 ws0">具有显著优势<span class="ff3">。</span></div><div class="t m0 x1 h2 yc ff2 fs0 fc0 sc0 ls0 ws0">三<span class="ff3">、<span class="ff1">Carsim-Simulink<span class="_ _0"> </span></span></span>联合仿真</div><div class="t m0 x1 h2 yd ff2 fs0 fc0 sc0 ls0 ws0">为了验证<span class="_ _1"> </span><span class="ff1">MPC<span class="_ _0"> </span></span>主动悬架的控制效果<span class="ff4">，</span>我们采用<span class="_ _1"> </span><span class="ff1">Carsim<span class="_ _0"> </span></span>和<span class="_ _1"> </span><span class="ff1">Simulink<span class="_ _0"> </span></span>进行联合仿真<span class="ff3">。<span class="ff1">Carsim<span class="_ _0"> </span></span></span>具有</div><div class="t m0 x1 h2 ye ff2 fs0 fc0 sc0 ls0 ws0">更加真实的动力学模型<span class="ff4">，</span>使得仿真结果更加准确<span class="ff3">。</span>在仿真中<span class="ff4">，</span>我们使用<span class="_ _1"> </span><span class="ff1">C<span class="_ _0"> </span></span>级路面进行测试<span class="ff3">。</span></div><div class="t m0 x1 h2 yf ff2 fs0 fc0 sc0 ls0 ws0">四<span class="ff3">、<span class="ff1">MPC<span class="_ _0"> </span></span></span>控制器在<span class="_ _1"> </span><span class="ff1">Simulink<span class="_ _0"> </span></span>中的实现</div><div class="t m0 x1 h2 y10 ff2 fs0 fc0 sc0 ls0 ws0">在<span class="_ _1"> </span><span class="ff1">Simulink<span class="_ _0"> </span></span>中<span class="ff4">，</span>我们使用<span class="_ _1"> </span><span class="ff1">mfunction<span class="_ _0"> </span></span>代码编写<span class="_ _1"> </span><span class="ff1">MPC<span class="_ _0"> </span></span>控制算法<span class="ff3">。</span>通过定义代价函数和约束条件<span class="ff4">，</span></div><div class="t m0 x1 h2 y11 ff2 fs0 fc0 sc0 ls0 ws0">我们可以求解出最优的控制序列<span class="ff3">。</span>在<span class="_ _1"> </span><span class="ff1">Simulink<span class="_ _0"> </span></span>中<span class="ff4">，</span>我们可以方便地观察和控制仿真过程<span class="ff4">，</span>以及分析</div><div class="t m0 x1 h2 y12 ff2 fs0 fc0 sc0 ls0 ws0">仿真结果<span class="ff3">。</span></div><div class="t m0 x1 h2 y13 ff2 fs0 fc0 sc0 ls0 ws0">五<span class="ff3">、</span>模型对比及性能指标</div><div class="t m0 x1 h2 y14 ff2 fs0 fc0 sc0 ls0 ws0">为了评估<span class="_ _1"> </span><span class="ff1">MPC<span class="_ _0"> </span></span>主动悬架的性能<span class="ff4">，</span>我们对比了主被动悬架的簧载质量加速度<span class="ff3">、</span>侧倾角速度<span class="ff3">、</span>俯仰角速度</div><div class="t m0 x1 h2 y15 ff2 fs0 fc0 sc0 ls0 ws0">等变量<span class="ff3">。</span>通过这些变量的对比<span class="ff4">，</span>我们可以清晰地观察到<span class="_ _1"> </span><span class="ff1">MPC<span class="_ _0"> </span></span>控制器的控制效果<span class="ff3">。</span></div><div class="t m0 x1 h2 y16 ff2 fs0 fc0 sc0 ls0 ws0">在<span class="_ _1"> </span><span class="ff1">matlab<span class="_ _0"> </span></span>代码中<span class="ff4">，</span>我们包括画图代码<span class="ff4">，</span>将悬架性能指标绘制出来<span class="ff3">。</span>这些图表可以直观地反映<span class="_ _1"> </span><span class="ff1">MPC<span class="_ _0"> </span></span>主</div><div class="t m0 x1 h2 y17 ff2 fs0 fc0 sc0 ls0 ws0">动悬架的性能优势<span class="ff3">。</span></div><div class="t m0 x1 h2 y18 ff2 fs0 fc0 sc0 ls0 ws0">六<span class="ff3">、</span>结果与讨论</div><div class="t m0 x1 h2 y19 ff2 fs0 fc0 sc0 ls0 ws0">通过<span class="_ _1"> </span><span class="ff1">Carsim-Simulink<span class="_ _0"> </span></span>联合仿真<span class="ff4">，</span>我们验证了<span class="_ _1"> </span><span class="ff1">MPC<span class="_ _0"> </span></span>主动悬架的控制效果<span class="ff3">。</span>与主被动悬架相比<span class="ff4">，</span></div><div class="t m0 x1 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">MPC<span class="_ _0"> </span><span class="ff2">主动悬架在簧载质量加速度<span class="ff3">、</span>侧倾角速度<span class="ff3">、</span>俯仰角速度等性能指标上表现出显著优势<span class="ff3">。</span>这表明</span></div><div class="t m0 x1 h2 y1b ff1 fs0 fc0 sc0 ls0 ws0">MPC<span class="_ _0"> </span><span class="ff2">控制器能够更好地优化悬架系统的性能<span class="ff4">，</span>提高汽车的行驶性能和乘坐舒适性<span class="ff3">。</span></span></div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>