Autonomous_Guidance_MPC_and_LQR-LMI:自动驾驶汽车的运动学MPC和动态LPV-LQR状态反馈控制-源码

上传者: 42173205 | 上传时间: 2021-09-24 22:15:58 | 文件大小: 306KB | 文件类型: ZIP
运动学MPC和动态增益调度状态反馈,用于控制自动驾驶汽车 该项目使您可以使用高级控制理论来解决自主制导问题。 该项目的创新部分是使用运动车辆模型的Takagi-Sugeno(TS)表示。 这使我们能够将非线性优化问题解决为伪线性问题,从而在每次优化时都实现了非常低的耗时。 先决条件 要运行该项目,您需要安装Matlab 2017b或更高版本以及YALMIP。 此外,有必要安装gurobi求解器以执行线性优化。 正在安装 要安装软件包,请参考以下链接: 描述 车辆型号 已经使用了两种不同的模型。 一个用于运动控制,另一个用于动态控制。 运动学模型称为车辆质量点模型。 动态模型为单轨自行车模型和轮胎模型的动力学模型。 轨迹规划 我们使用基于多项式的算法以离线方式计算参考。 该阶段在每个时刻提供对控制器的所需参考。 运动MPC 此时,将在每次控制迭代中构建并求解模型预测控制器,以找到最佳控制动

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