Robust Safe Control Synthesis with Disturbance Observer-Based Control Barrier Functions

被引:33
作者
Das, Ersin [1 ]
Murray, Richard M. [1 ]
机构
[1] CALTECH, 1200 East Calif Blvd, Pasadena, CA 91125 USA
来源
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC) | 2022年
关键词
STABILIZATION;
D O I
10.1109/CDC51059.2022.9993032
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In a complex real-time operating environment, external disturbances and uncertainties adversely affect the safety, stability, and performance of dynamical systems. This paper presents a robust stabilizing safety-critical controller synthesis framework with control Lyapunov functions (CLFs) and control barrier functions (CBFs) in the presence of disturbance. A high-gain input observer method is adapted to estimate the time-varying unmodelled dynamics of the CBF with an error bound using the first-order time derivative of the CBF. This approach leads to an easily tunable low-order disturbance estimator structure with a design parameter as it utilizes only the CBF constraint. The estimated unknown input and associated error bound are used to ensure robust safety by formulating a CLF-CBF quadratic program. The proposed method is applicable to both relative degree one and higher relative degree CBF constraints. The efficacy of the proposed approach is demonstrated using a numerical simulations of an adaptive cruise control system and a Segway platform with an external disturbance.
引用
收藏
页码:5566 / 5573
页数:8
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