Multi-Objective Co-Optimization of FlexRay-Based Distributed Control Systems

Debayan Roy, Licong Zhang, Wanli Chang, Dip Goswami, S. Chakraborty
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引用次数: 36

Abstract

Recently, research on control and architecture co- design has been drawing increasingly more attention. This is because these techniques integrate the design of the controllers and the architecture and explore the characteristics on both sides to achieve more efficient design of embedded control systems. However, there still exist several challenges like the large design space and inadequate trade-off opportunities for different objectives like control performance and resource utilization. In this paper, we propose a co-optimization approach for FlexRay-based distributed control systems, that synthesizes both the controllers and the task and communication schedules. This approach exploits some FlexRay protocol specific characteristics to reduce the complexity of the whole optimization problem. This is done by employing a customized control design and a nested two-layered optimization technique. Therefore, compared to existing methods, the proposed approach is more scalable. It also allows multi-objective optimization taking into account both the overall control performance and the bus resource utilization. This approach generates a Pareto front representing the trade-offs between these two, which allows the engineers to make suitable design choices.
基于flexray的分布式控制系统多目标协同优化
近年来,控制与结构协同设计的研究越来越受到人们的重视。这是因为这些技术将控制器的设计与体系结构的设计相结合,探索两者的特点,从而实现更高效的嵌入式控制系统设计。然而,仍然存在一些挑战,如较大的设计空间和对不同目标(如控制性能和资源利用率)的权衡机会不足。在本文中,我们提出了一种基于flexray的分布式控制系统的协同优化方法,该方法综合了控制器以及任务和通信调度。这种方法利用了FlexRay协议的一些特定特性来降低整个优化问题的复杂性。这是通过采用定制的控件设计和嵌套的两层优化技术来实现的。因此,与现有方法相比,该方法具有更强的可扩展性。它还允许考虑总体控制性能和总线资源利用率的多目标优化。这种方法产生了一个帕累托前沿,代表了这两者之间的权衡,这使得工程师能够做出合适的设计选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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