用屏障状态提升不确定非线性系统的安全自适应控制性能
Safety Embedded Adaptive Control Using Barrier States
- 引入屏障状态增强带参数不确定的动态模型
- 控制器确保原系统安全控制且满足性能指标
- 适用于无人机、自适应巡航等需安全控制场景
本文研究了屏障状态（Barrier States, BaS）在安全非线性自适应控制中的应用。所提框架为具有参数不确定性的系统推导屏障状态，并将其融入不确定动力学模型中。基于控制李雅普诺夫函数方法，设计一种自适应非线性控制策略，以稳定增广系统。理论分析表明，该控制器能确保原系统控制动作的安全性，同时达成预定性能目标。通过在多种系统上的仿真验证了方法的有效性，包括受未知阻力影响的平面四旋翼无人机和自适应巡航控制系统，并与现有方法进行了对比。
原文摘要 · Abstract (English)
In this work, we explore the application of barrier states (BaS) in the realm of safe nonlinear adaptive control. Our proposed framework derives barrier states for systems with parametric uncertainty, which are augmented into the uncertain dynamical model. We employ an adaptive nonlinear control strategy based on a control Lyapunov functions approach to design a stabilizing controller for the augmented system. The developed theory shows that the controller ensures safe control actions for the original system while meeting specified performance objectives. We validate the effectiveness of our approach through simulations on diverse systems, including a planar quadrotor subject to unknown drag forces and an adaptive cruise control system, for which we provide comparisons with existing methodologies.
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