Kalaycioglu Serdar, De Ruiter Anton
Department of Aerospace Engineering, Toronto Metropolitan University, Toronto, ON, Canada.
Front Robot AI. 2023 Jun 5;10:1181128. doi: 10.3389/frobt.2023.1181128. eCollection 2023.
In the past 2 decades, there has been increasing interest in autonomous multi-robot systems for space use. They can assemble space structures and provide services for other space assets. The utmost significance lies in the performance, stability, and robustness of these space operations. By considering system dynamics and constraints, the Model Predictive Control (MPC) framework optimizes performance. Unlike other methods, standard MPC can offer greater robustness due to its receding horizon nature. However, current literature on MPC application to space robotics primarily focuses on linear models, which is not suitable for highly non-linear multi-robot systems. Although Nonlinear MPC (NMPC) shows promise for free-floating space manipulators, current NMPC applications are limited to unconstrained non-linear systems and do not guarantee closed-loop stability. This paper introduces a novel approach to NMPC using the concept of passivity to multi-robot systems for space applications. By utilizing a passivity-based state constraint and a terminal storage function, the proposed PNMPC scheme ensures closed-loop stability and a superior performance. Therefore, this approach offers an alternative method to the control Lyapunov function for control of non-linear multi-robot space systems and applications, as stability and passivity exhibit a close relationship. Finally, this paper demonstrates that the benefits of passivity-based concepts and NMPC can be combined into a single NMPC scheme that maintains the advantages of each, including closed-loop stability through passivity and good performance through one-line optimization in NMPC.
在过去20年里，人们对用于太空的自主多机器人系统越来越感兴趣。它们可以组装太空结构并为其他太空资产提供服务。这些太空操作的性能、稳定性和鲁棒性至关重要。通过考虑系统动力学和约束条件，模型预测控制（MPC）框架可优化性能。与其他方法不同，标准MPC由于其滚动时域特性可提供更高的鲁棒性。然而，目前关于MPC应用于太空机器人技术的文献主要集中在线性模型上，这不适用于高度非线性的多机器人系统。尽管非线性MPC（NMPC）在自由漂浮太空操纵器方面显示出前景，但目前的NMPC应用仅限于无约束非线性系统，且不能保证闭环稳定性。本文针对太空应用的多机器人系统，引入一种基于无源性概念的新型NMPC方法。通过利用基于无源性的状态约束和终端存储函数，所提出的PNMPC方案确保了闭环稳定性和卓越性能。因此，由于稳定性和无源性存在密切关系，该方法为非线性多机器人太空系统及应用的控制提供了一种替代控制李雅普诺夫函数的方法。最后，本文证明基于无源性概念和NMPC的优点可以结合到一个单一的NMPC方案中，该方案兼具两者的优势，包括通过无源性实现闭环稳定性以及通过NMPC中的在线优化实现良好性能。
