基于全状态依赖事件触发方法的高速列车运动受限间歇控制。

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Meng Yang , Junguo Wang , Bin Liu
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引用次数: 0

摘要

针对高速列车运行中能量消耗最小化、速度跟踪精度提高的问题,提出了基于输入约束的全状态依赖事件触发非周期间歇控制策略。首先,建立了基于多质点的HST动力学模型,将巡航控制问题转化为误差渐近收敛问题;其次,在存在和不存在外界干扰的情况下,分别设计受限FE-AIC (RFE-AIC)控制器,实现对目标的跟踪;所提出的控制方案不仅基于控制输入约束,而且采用完全状态事件依赖的间歇控制。给出了RFE-AIC格式和确定参数的条件,保证了理想跟踪速度和平衡点处耦合器偏差的稳定性。最后,通过数值仿真验证了该方法在巡航控制中的有效性。实验证明,与自触发和保证最优巡航控制方法相比,RFE-AIC具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The restricted intermittent control for high-speed train movement via the full state dependent event-triggered method
In this paper, the full state dependent event-triggered aperiodic intermittent control (FE-AIC) strategy based on input constraints is introduced to minimize energy consumption and enhance speed tracking accuracy in the high-speed train (HST) operation. Firstly, a dynamic model based on multi-mass-point (MMP) for HST has been established, transforming the cruise control problem into an error asymptotic convergence problem. Secondly, restricted FE-AIC (RFE-AIC) controller is designed separately in the presence and absence of external disturbances to realize tracking objects. The proposed control scheme is not only based on control input constraints, but also intermittent control with full state event dependence. The RFE-AIC scheme and the conditions for determining parameters are given, which ensures the stability of the ideal tracking speed and coupler deviation at the equilibrium point. Eventually, the availability of the proposed method in cruise control is confirmed through numerical simulations. It is proved that the RFE-AIC has better performance compared with the self-triggered and guaranteed optimal cruise control methods.
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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