Robust Coordinated Hybrid Source Seeking With Obstacle Avoidance in Multivehicle Autonomous Systems
成果类型:
Article
署名作者:
Poveda, Jorge, I; Benosman, Mouhacine; Teel, Andrew R.; Sanfelice, Ricardo G.
署名单位:
University of Colorado System; University of Colorado Boulder; University of California System; University of California Santa Barbara; University of California System; University of California Santa Cruz
刊物名称:
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
ISSN/ISSBN:
0018-9286
DOI:
10.1109/TAC.2021.3056365
发表日期:
2022
页码:
706-721
关键词:
Vehicle dynamics
Collision avoidance
navigation
CONVERGENCE
Aerospace electronics
nonlinear dynamical systems
Adaptive control
adaptive algorithms
nonlinear control systems
unmanned autonomous vehicles
摘要:
In multivehicle autonomous systems that operate under unknown or adversarial environments, it is a challenging task to simultaneously achieve source seeking and obstacle avoidance. Indeed, even for single-vehicle systems, smooth time-invariant feedback controllers based on navigation or barrier functions have been shown to be highly susceptible to arbitrarily small jamming signals that can induce instability in the closed-loop system, or that are able to stabilize spurious equilibria in the operational space. When the location of the source is further unknown, adaptive smooth source seeking dynamics based on averaging theory may suffer from similar limitations. In this article, we address this problem by introducing a class of novel distributed hybrid model-free controllers, that achieve robust source seeking and obstacle avoidance in multivehicle autonomous systems, with vehicles characterized by nonlinear continuous-time dynamics stabilizable by hybrid feedback. The hybrid source seeking law switches between a family of cooperative gradient-free controllers, derived from potential fields that satisfy mild invexity assumptions. The stability and robustness properties of the closed-loop system are analyzed using Lyapunov tools and singular perturbation theory for set-valued hybrid dynamical systems. The theoretical results are validated via numerical and experimental tests.