移动机器人模型预测控制方法:以灌溉渠为例

Roza Ranjbar, Javier G. Martin, J. Maestre, L. Etienne, E. Duviella, E. Camacho
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引用次数: 0

摘要

针对灌溉渠动态不确定的控制问题,提出了一种结合移动机器人的随机模型预测控制方法。我们对预测视界的采样时间施加了严格的约束,使控制器计算出机器人为MPC控制器收集新测量值的最佳路径。采用ASCE测试运河的数值模型作为案例研究,验证了在回路中加入机器人的MPC策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mobile Robot Model Predictive Control Approach: Case Study of an Irrigation Canal
We propose a stochastic model predictive control (SMPC) in combination with a mobile robot to address a control problem for an irrigation canal with uncertain dynamics. We impose tightened constraints over the sampling time of the prediction horizon to make the controller calculate the best route for the robot to gather new measurements for the MPC controller. This MPC strategy with a robot in the loop is validated using a numerical model of an ASCE Test Canal as a case study.
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