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Main Authors: Liu, Zihan, Ni, Yuan-Hua
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2503.10164
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author Liu, Zihan
Ni, Yuan-Hua
author_facet Liu, Zihan
Ni, Yuan-Hua
contents This paper addresses the safety challenges in impulsive systems, where abrupt state jumps introduce significant complexities into system dynamics. A unified framework is proposed by integrating Quadratic Programming (QP), Control Barrier Functions (CBFs), and adaptive gain mechanisms to ensure system safety during impulsive events. The CBFs are constructed to enforce safety constraints by capturing the system's continuous dynamics and the effects of impulsive state transitions. An adaptive gain mechanism dynamically adjusts control inputs based on the magnitudes of the impulses and the system's proximity to safety boundaries, maintaining safety during instantaneous state jumps. A tailored QP formulation incorporates CBFs constraints and adaptive gain adjustments, optimizing control inputs while ensuring compliance with safety-critical requirements. Theoretical analysis establishes the boundedness, continuity, and feasibility of the adaptive gain and the overall framework. The effectiveness of the method is demonstrated through simulations on a robotic manipulator, showcasing its practical applicability to impulsive systems with state jumps.
format Preprint
id arxiv_https___arxiv_org_abs_2503_10164
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Safety Control of Impulsive Systems with Control Barrier Functions and Adaptive Gains
Liu, Zihan
Ni, Yuan-Hua
Optimization and Control
This paper addresses the safety challenges in impulsive systems, where abrupt state jumps introduce significant complexities into system dynamics. A unified framework is proposed by integrating Quadratic Programming (QP), Control Barrier Functions (CBFs), and adaptive gain mechanisms to ensure system safety during impulsive events. The CBFs are constructed to enforce safety constraints by capturing the system's continuous dynamics and the effects of impulsive state transitions. An adaptive gain mechanism dynamically adjusts control inputs based on the magnitudes of the impulses and the system's proximity to safety boundaries, maintaining safety during instantaneous state jumps. A tailored QP formulation incorporates CBFs constraints and adaptive gain adjustments, optimizing control inputs while ensuring compliance with safety-critical requirements. Theoretical analysis establishes the boundedness, continuity, and feasibility of the adaptive gain and the overall framework. The effectiveness of the method is demonstrated through simulations on a robotic manipulator, showcasing its practical applicability to impulsive systems with state jumps.
title Safety Control of Impulsive Systems with Control Barrier Functions and Adaptive Gains
topic Optimization and Control
url https://arxiv.org/abs/2503.10164