论文标题
在不确定环境中的安全轨迹跟踪
Safe Trajectory Tracking in Uncertain Environments
论文作者
论文摘要
在轨迹跟踪问题的模型预测控制（MPC）中，不可行的参考轨迹和A-Priori未知约束可能会导致繁琐的设计，攻击性跟踪以及递归可行性的丧失。例如，在尚不清楚A-Priori的约束的情况下，在移动系统的轨迹跟踪应用中就是这种情况。在本文中，我们提出了一个称为模型预测灵活轨迹跟踪控制（MPFTC）的新框架，该框架可放宽轨迹跟踪要求。此外，在存在A-Priori未知约束的情况下，我们可以适应递归的可行性，这可能使参考轨迹不可行。在提议的框架中，始终保证约束满意度，而跟踪参考轨迹与约束满意度一样好，从而简化了控制器设计并降低了可能的攻击性跟踪行为。提出的框架用三个数字示例进行了说明。
In Model Predictive Control (MPC) formulations of trajectory tracking problems, infeasible reference trajectories and a-priori unknown constraints can lead to cumbersome designs, aggressive tracking, and loss of recursive feasibility. This is the case, for example, in trajectory tracking applications for mobile systems in the presence of constraints which are not fully known a-priori. In this paper, we propose a new framework called Model Predictive Flexible trajectory Tracking Control (MPFTC), which relaxes the trajectory tracking requirement. Additionally, we accommodate recursive feasibility in the presence of a-priori unknown constraints, which might render the reference trajectory infeasible. In the proposed framework, constraint satisfaction is guaranteed at all times while the reference trajectory is tracked as good as constraint satisfaction allows, thus simplifying the controller design and reducing possibly aggressive tracking behavior. The proposed framework is illustrated with three numerical examples.
