An anti-trackslip path tracking algorithm for steel box girder inspection robot based on model prediction control

Zhenbo Yang, Lei Xue, Peng Wang, Shaobin Wei, He Gao, Yufang Wen, Yong Tao
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Abstract

An anti-trackslip path tracking algorithm for steel box girder inspection robot based on model prediction (MPC) is proposed in this paper. This algorithm is oriented to the actual needs of the automatic inspection of steel box girder of super large bridges. It solves the slippage problem of the inspection robot because of the wear of driving wheels and slippery contact. The kinematic models of longitudinal and lateral slippage were established and corrected after analyzing the robot sliding control and slippage parameter estimation methods. The robot system error dynamic model and the error model based on state extension were proposed by overall considering control constraints. The robot’s optimized objective function was constructed to convert MPC problem into quadratic programming. Finally, path tracking simulations were performed on the inspection robot under pure rolling and sliding conditions, respectively, using the improved MPC (IMPC) algorithm and the front-wheel feedback algorithm. The comparison showed that the IMPC algorithm exceeded the front-wheel feedback algorithm based on geometrical tracking in tracking precision, proving the effectiveness of the proposed IMPC in anti-trackslip path tracking.
基于模型预测控制的钢箱梁检测机器人防滑轨路径跟踪算法
提出了一种基于模型预测(MPC)的钢箱梁检测机器人防滑轨路径跟踪算法。该算法是针对特大型桥梁钢箱梁自动检测的实际需要而设计的。解决了检测机器人因驱动轮磨损和接触滑滑而产生的打滑问题。在分析机器人滑动控制和滑动参数估计方法的基础上,建立了机器人纵向和横向滑动的运动学模型并进行了修正。在综合考虑控制约束的基础上,提出了机器人系统误差动态模型和基于状态扩展的误差模型。构造机器人的优化目标函数,将MPC问题转化为二次规划问题。最后,分别采用改进的MPC (IMPC)算法和前轮反馈算法对检测机器人在纯滚动和滑动条件下进行了路径跟踪仿真。对比结果表明,IMPC算法在跟踪精度上优于基于几何跟踪的前轮反馈算法,证明了该算法在抗滑轨跟踪中的有效性。
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