提出实时非线性模型预测控制框架，提升重载滑移平台轨迹跟踪精度与稳定性。
Real-Time Nonlinear Model Predictive Control of Heavy-Duty Skid-Steered Mobile Platform for Trajectory Tracking Tasks
- 采用多射击非线性模型预测控制，融合多传感器数据实现实时优化。
- 在多种轨迹跟踪任务中表现优异，速度与精度显著优于现有方法。
- 适用于高动态复杂环境下的重载移动平台控制，对安全运行至关重要。
本文提出一种面向重载滑移转向移动平台轨迹跟踪任务的实时最优控制框架。控制器的高实时性对系统在不确定性与扰动影响下的安全性至关重要，需及时补偿以保证稳定性能。本文设计了一种多射击非线性模型预测控制框架，结合多种传感器读数，在实际系统中实现极高的控制精度与实时性。控制器在不同轨迹跟踪任务中验证，展现出卓越的性能表现。相较于文献中已有的滑移转向平台非线性模型预测控制器，本方法在控制效果上具有显著提升。
原文摘要 · Abstract (English)
This paper presents a framework for real-time optimal controlling of a heavy-duty skid-steered mobile platform for trajectory tracking. The importance of accurate real-time performance of the controller lies in safety considerations of situations where the dynamic system under control is affected by uncertainties and disturbances, and the controller should compensate for such phenomena in order to provide stable performance. A multiple-shooting nonlinear model-predictive control framework is proposed in this paper. This framework benefits from suitable algorithm along with readings from various sensors for genuine real-time performance with extremely high accuracy. The controller is then tested for tracking different trajectories where it demonstrates highly desirable performance in terms of both speed and accuracy. This controller shows remarkable improvement when compared to existing nonlinear model-predictive controllers in the literature that were implemented on skid-steered mobile platforms.
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