基于空间模型预测控制的矿井车辆避障控制器的研究

Research on obstacle avoidance control of mine vehicles based on spatial model predictive control

针对矿井车辆在巷道实时避障过程中参考轨迹的平滑性问题以及在轨迹跟踪过程中转向角突然变化对矿井车辆结构和转向部件造成损伤问题,设计了1种改进的基于空间模型预测控制(SMPC)算法的矿井车辆避障控制器。该设计结合模型预测控制原理和曲线坐标系,将笛卡尔坐标系下的基于时间t的车辆运动学模型转换成曲线坐标系下基于空间s的偏差模型,采用泰勒线性化处理和欧拉法离散,推导出矿井车辆偏差模型的预测方程;在轨迹跟踪部分建立目标函数优化车辆转向曲率的一阶、二阶导数和横向位移偏差值,在轨迹重规划部分建立目标函数优化横向偏差值及其一阶、二阶导数,并结合障碍物信息和巷道边界信息设置边界函数;将目标函数转换为二次规划问题求解最优控制序列。模拟井下巷道环境搭建仿真平台,对本文提出的矿井车辆避障控制器进行实时仿真验证。结果表明,改进后的控制器在轨迹跟踪方面能够保证车辆与参考轨迹之间的横向位移偏差控制在0.2 m以内,航向角偏差控制在0.09 rad以内;与传统的MPC控制算法相比,改进后的控制器具有更加优秀的精确性和平稳性;在实时避障方面,控制器控制性能会受到道路曲率的影响,但无论是在单个障碍物还是连续多个障碍物情况下,车辆都能够避开障碍物,获得平滑的转向输入和平滑、精确的行驶轨迹。

Aiming at the problem of the reference track smoothness of mine vehicle in the real-time obstacle avoidance process of roadway and the damage caused by the sudden change of turning angle to mine vehicle structure and steering components in the track tracking process,an improved mine vehicle obstacle avoidance controller based on the spatial model predictive control(SMPC)algorithm was designed.The design process of mine vehicle obstacle avoidance controller is as follows.Firstly,combining with model predictive control principle and Curvilinear coordinate system,the Cartesian coordinates of the vehicle kinematic model based on time t is converted into the Curvilinear Coordinates of deviation model based on space s.Mine vehicle deviation model predictive equation is deduced by using Taylor method to linearize and Euler method to discrete.Secondly,in the part of track tracking,the objective function is set to optimize the first and second derivatives of vehicle steering curvature and lateral displacement deviation.While in the part of trajectory reprogramming,the boundary function is set based on obstacle information and roadway boundary information,and the objective function is set to optimize the transverse deviation value and its first and second derivatives.Finally,the objective function is transformed into quadratic programming problem to solve the optimal control sequence.A simulation platform was built to simulate underground roadway environment and a real-time simulation verification was carried out on the proposed mine vehicle obstacle avoidance controller.The results show that the improved controller can keep the lateral displacement deviation between the vehicle and the reference trajectory within 0.2 m and the heading angle deviation within 0.09 rad in track tracking.Compared with the traditional MPC control algorithm,the improved controller has a better accuracy and stability.In terms of real-time obstacle avoidance,the control performance of the controller is affected by the road curvature.However,no matter in the case of single obstacle or continuous multiple obstacles,the vehicle can avoid the obstacle and obtain a smooth steering input and a smooth and accurate driving track.