Multi-Rate Control Design Leveraging Control Barrier Functions and Model Predictive Control Policies

被引:28
|
作者
Rosolia, Ugo [1 ]
Ames, Aaron D. [1 ]
机构
[1] CALTECH, AMBER Lab, Pasadena, CA 91030 USA
来源
IEEE CONTROL SYSTEMS LETTERS | 2021年 / 5卷 / 03期
基金
美国国家科学基金会;
关键词
Predictive control; autonomous systems; Lyapunov methods;
D O I
10.1109/LCSYS.2020.3008326
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 this letter we present a multi-rate control architecture for safety critical systems. We consider a high level planner and a low level controller which operate at different frequencies. This multi-rate behavior is described by a piecewise nonlinear model which evolves on a continuous and a discrete level. First, we present sufficient conditions which guarantee recursive constraint satisfaction for the closed-loop system. Afterwards, we propose a control design methodology which leverages Control Barrier Functions (CBFs) for low level control and Model Predictive Control (MPC) policies for high level planning. The control barrier function is designed using the full nonlinear dynamical model and the MPC is based on a simplified planning model. When the nonlinear system is control affine and the high level planning model is linear, the control actions are computed by solving convex optimization problems at each level of the hierarchy. Finally, we show the effectiveness of the proposed strategy on a simulation example, where the low level control action is updated at a higher frequency than the high level command.
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页码:1007 / 1012
页数:6
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