Optimization-based Multi-actuator Control for Autonomous Vehicles

被引:1
|
作者
Kovacs, Adorjan [1 ]
Vajk, Istvan [1 ]
机构
[1] Budapest Univ Technol & Econ, Dept Automat & Appl Informat, Budapest, Hungary
来源
INES 2021: 2021 IEEE 25TH INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS | 2021年
关键词
Autonomous Driving; Multi-Actuator Control; Internal Model Control; Nonlinear Control Convex Optimization;
D O I
10.1109/INES52918.2021.9512906
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents a novel controller structure for multi-actuator control of autonomous vehicles. The proposed cascade structure establishes an internal model controller (IMC) for force and moment control to gain a robust solution. An optimization-based allocation algorithm generates the desired force and moment. The optimization problem is formulated to be a second-order cone programming (SOCP) problem. In this method, the nonlinearities, physical limitations are considered. Different control rules are created based on physical expressions focusing on minimizing intuitively tuned parameters. The former and the novel rules are examined, compared, and evaluated by simulations. The presented simulation results show that the proposed structure is robust against external and internal parameter changes and disturbances.
引用
收藏
页数:6
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