有向安全协调中的网络化可容许性保持控制
Networked Admissibility-Preserving Control for Directed Safe Coordination
Abhinav Sinha, Lohitvel Gopikannan, Shashi Ranjan Kumar
AI 速读 基于摘要
针对固定有根有向图上输入受限的标量智能体,提出网络化可容许性保持控制架构,使各智能体在异构非对称输入界下安全协调进入共同移动输出走廊。
eess.SY · cs.MA · cs.RO · math.DS
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This paper addresses safe coordination of scalar agents with constrained input dynamics over fixed rooted digraphs. We propose a networked Admissibility-Preserving Control (APC) architecture for a common moving output corridor under heterogeneous asymmetric input bounds, wherein the Admissibility-Preserving Input Realization (APIR) generates the physical inputs. In logarithmic barrier coordinates, the closed-loop dynamics form an exact cascade of exponentially decaying realization errors and directed consensus dynamics. We derive direction-specific compatibility conditions that guarantee uniform corridor and input margins, bounded commands, unique complete solutions, and exponential consensus for compact initial sets. The closed-form expression for the agreement value quantifies the effect of the initial APIR mismatch. Under the corresponding compatibility conditions, partial pinning guarantees safe reference tracking whenever the root component contains at least one informed agent. Simulations illustrate the coordination guarantees.