稳定模型预测控制器在类车农业机器人路径跟踪中的应用

Román Comelli, Sorin Olaru, María M. Seron, Ernesto Kofman
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引用次数: 0

摘要

这项研究通过有限控制集模型预测控制(FCS-MPC)策略解决了类似汽车的农业机器人的路径跟踪问题,该策略考虑了由有限元素组成的集合中的控制行动。用一对内-外集合取代经典控制不变集的稳定 MPC 方案的最新成果得到了扩展,以保持不同控制和预测视野下的稳定性,并用于上述应用。所提出的方法特别简单,可以明确处理非线性和约束条件,但牺牲了车辆转向系统的分辨率,这在实践中不会影响控制器的性能。除了介绍控制方法外,还将进行模拟并与另一种非线性 MPC 策略进行比较,以说明所提方案的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Application of a stabilizing model predictive controller to path following for a car‐like agricultural robot

Application of a stabilizing model predictive controller to path following for a car‐like agricultural robot
This work addresses the problem of path following for a car‐like agricultural robot by means of a finite control set model predictive control (FCS‐MPC) strategy that considers the control actions in a set composed of a limited amount of elements. Recent results on a stabilizing MPC formulation that replaces the classical control invariant set by a pair of inner‐outer sets are extended to preserve stability properties with different control and prediction horizons and are then used for the aforementioned application. Being particularly simple, the presented approach can explicitly deal with nonlinearities and constraints at the expense of resolution in the vehicle steering system, which in practice does not affect the controller performance as will be shown. In addition to describing the control method, simulations and a comparison with another nonlinear MPC strategy are presented to illustrate the advantages of the proposed scheme.
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