Robust Synergistic Hybrid Feedback

• 成果类型: Article
• 署名作者: Casau, Pedro; Sanfelice, Ricardo G.; Silvestre, Carlos
• 署名单位: Universidade de Aveiro; Universidade de Aveiro; University of California System; University of California Santa Cruz; University of Macau; Universidade de Lisboa
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3416194
• 发表日期: 2024
• 页码: 8555-8570
• 关键词: Collision avoidance; Closed loop systems; uncertainty; switches; logic; vectors; robots; Adaptive control; hybrid systems; robotics; uncertain systems

摘要

Synergistic hybrid feedback refers to a collection of feedback laws that allow for the global asymptotic stabilization of a compact set through the following switching logic: given a collection of Lyapunov functions that are indexed by a logic variable, whenever the currently selected Lyapunov function exceeds the value of another function in the collection by a given margin, then a switch to the corresponding feedback law is triggered. This kind of feedback has been under development over the past decade, and it has led to multiple solutions for global asymptotic stabilization problems on compact manifolds. The contributions of this article include a synergistic controller design in which the logic variable is not necessarily constant between jumps, a synergistic hybrid feedback that is able to tackle the presence of parametric uncertainty, backstepping of adaptive synergistic hybrid feedback, and a demonstration of the proposed solutions to the problem of global obstacle avoidance.