Research on path tracking control of mobile storage robot based on model predictive control and linear quadratic regulator

Hao Chen, Xuelin Wang, Lide Zhao, Ru Jiang, Baigunchekov Zhumadil
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Abstract

To achieve that the mobile warehouse robot follows the given desired path quickly and smoothly, the MPC and LQR steering control algorithms are applied based on the lateral kinematic constraints of the vehicle. First, the Ackermann kinematic modelling of the mobile platform is performed. The nonlinear model is linearized and discretized to create a discrete state space model of the mobile robot. Under the same conditions, a lateral control system based on MPC and LQR is designed for the mobile robot. A performance comparison of parameters such as different vehicle speeds, straightline trajectory tracking, curve trajectory tracking and algorithm consumption time is performed. The simulation shows that the LQR and MPC controllers can calculate the vehicle's steering angle in real time according to the road curvature and drive according to the preset desired path.
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基于模型预测控制和线性二次型调节器的移动存储机器人路径跟踪控制研究
为了使移动仓库机器人快速平稳地沿着给定路径运动,基于车辆的横向运动约束,应用MPC和LQR转向控制算法。首先,对移动平台进行Ackermann运动学建模。对非线性模型进行线性化和离散化,建立了移动机器人的离散状态空间模型。在相同的条件下,设计了基于MPC和LQR的移动机器人横向控制系统。对不同车速、直线轨迹跟踪、曲线轨迹跟踪和算法消耗时间等参数进行了性能比较。仿真结果表明,LQR和MPC控制器可以根据道路曲率实时计算出车辆的转向角度,并按照预设的期望路径行驶。
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