基于能量耗散的智能车速逐次逼近算法*

Rui Zhang, Yulin Ma, Xiaofeng Liu
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引用次数: 1

摘要

提出了一种基于能量耗散的智能车速自适应逐次逼近算法。由于车辆动力系统类似于一系列耗散的质量/弹簧/阻尼系统,即系统能量最终衰减为零,因此将IVSA问题转化为基于能量存储功能的耗散控制设计。为了满足二次供应率的γ-性能,采用基于性能边界逐步改进的回溯Lyapunov方法建立了存储函数。利用SAA设计了一种耗散控制律,使γ的值逐步减小。在变加速度条件下进行了IVSA仿真,通过比较不同γ值下的纵向和横向跟踪误差和能量消耗,验证了IVSA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。
Energy dissipation based successive approximation algorithm for intelligent vehicle speed adaption*
This paper proposes a successive approximation algorithm (SAA) for intelligent vehicle speed adaption (IVSA) based on energy dissipation. As vehicle dynamical system resembles a series of mass/spring/damper systems that are dissipative, i.e., the energy of the system decays to zero eventually, the problem of IVSA is transformed into dissipative control design based on energy storage function. In order to satisfy the γ-performance with respect to the quadratic supply rate, the storage function is developed by using a backstepping based Lyapunov method based on a step-by-step improvement of performance bounds. A dissipative control law is designed by a SAA with a step-by-step reduction of the value of γ. The IVSA simulations are given under variable acceleration condition, whose performances are verified by the comparison of both longitudinal and lateral tracking errors and energy-consuming in different values of γ.
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