基于极值求联合仿真框架的钝化与性能优化及其在自适应巡航控制系统中的应用

Arash Rahnama, M. Xia, Shige Wang, P. Antsaklis
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引用次数: 7

摘要

本文将前人研究的输入输出变换钝化方法应用于自适应巡航控制系统,并分析了该系统的性能。利用称为极值搜索的在线优化方法的联合仿真框架用于确定钝化参数。众所周知,具有输入-输出时滞的系统不是被动的。此外,延迟在汽车系统中是不可避免的,并且通常出现在软件实现、通信单元以及驾驶员的行为中。我们的研究表明,采用我们的钝化方法,我们可以钝化时滞系统,并通过极值寻求联合仿真框架提高其整体性能。为了验证我们的工作,我们在CarSim和Simulink中给出了仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Passivation and performance optimization using an extremum seeking co-simulation framework with application to Adaptive Cruise Control systems
In this paper, we apply an input-output transformation passivation method developed in our previous work to an Adaptive Cruise Control system and analyze the system's performance. A co-simulation framework that makes use of an online optimization method called extremum-seeking is used to determine the passivation parameters. It is known that systems with input-output time-delays are not passive. Additionally, time-delays are unavoidable in automotive systems and commonly emerge in software implementations, communication units, as well as driver's behavior. We show that by using our passivation method, we can passivate a time-delay system and improve its overall performance by using an extremum-seeking co-simulation framework. To validate our work, we present simulation results in CarSim and Simulink.
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