Regulation of Nonholonomic Mobile Robots using Model Predictive Control:Set Point Stabilization, Path Following, and Distributed Control

在自主移动机器人的背景下，已提出将非线性模型预测控制(MPC)应用于设定值镇定、轨迹跟踪和路径跟踪等不同的控制任务。对于这些应用领域，充分稳定条件的问题可以在附加终端约束和/或成本的帮助下得到回答。由于只要考虑到障碍物或几个移动机器人，这些额外的(人工)成分就会受到限制，因此避免这些稳定性强制限制具有实际意义。在科学网络中，我们的目标是制定严格的稳定性保证，既不需要终端区域，也不需要终端限制。在这里，我们遵循一个三个阶段的程序：首先，我们专注于连续时间公式以及各个采样数据实现的设定点稳定。其次，基于所获得的结果，考虑路径跟踪任务，以使移动机器人能够避开静态障碍物。最后，我们用几个移动机器人考察了一个场景。在这一理论部分的侧翼，我们计划实施和测试所提出的MPC方案，并利用模拟和原型来测量它们的性能。拟议的项目将为从事MPC不同方面工作的早期研究人员建立一个合作平台，以便确定和促进未来的联合研究项目。

In the context of autonomous mobile robots, the application of nonlinear model predictive control (MPC) has been proposed for different control tasks such as set-point stabilization, trajectory tracking, and path following. For these application areas the question of sufficient stability conditions can be answered with the help of additional terminal constraints and / or costs. Since these additional (artificial) ingredients are restrictive as soon as obstacles or several mobile robots are taken into account, avoiding these stability enforcing constraints is of practical interest. Within the scientific network our goal is to develop rigorous stability guarantees that require neither terminal regions nor terminal constraints. Herein, we follow a three stage program: First, we focus on set point stabilization for continuous time formulations as well as for the respective sampled-data implementations. Secondly, based on the obtained results, we consider path following tasks in order to enable the mobile robots to circumvent static obstacles. And last, we investigate a setting with several mobile robots. Flanking this theoretical part, we plan to implement and test the proposed MPC schemes as well as measure their performance utilizing both simulations and prototypes. The proposed project shall establish a collaboration platform for early stage researchers working on different aspects of MPC, which will allow for identifying and fostering future joint research projects.