Flores Carlos, Muñoz Jorge, Monje Concepción A, Milanés Vicente, Lu Xiao-Yun
California PATH Program of the Institute of Transportation Studies, University of California Berkeley, Richmond, CA 94804, United States.
University Carlos III of Madrid, Systems Engineering and Automation Department, Avenida Universidad 30, 28911 Leganés, Madrid, Spain.
J Adv Res. 2020 Jun 17;25:181-189. doi: 10.1016/j.jare.2020.05.013. eCollection 2020 Sep.
This work deals with the control design and development of an automated car-following strategy that further increases robustness to vehicle dynamics uncertainties. The control algorithm is applied on a hierarchical architecture where high and low level control layers are designed for gap-control and desired acceleration tracking, respectively. A fractional-order controller is proposed due to its flexible frequency shape, fulfilling more demanding design requirements. The iso-damping loop property is sought, which yields a desired closed-loop stability that results invariant despite changes on the controlled plant gain. In addition, the graphical nature of the proposed design approach demonstrates its portability and applicability to any type of vehicle dynamics without complex reconfiguration. The algorithm benefits are validated in frequency and time domains, as well as through experiments on a real vehicle platform performing adaptive cruise control.
这项工作涉及一种自动跟车策略的控制设计与开发,该策略可进一步增强对车辆动力学不确定性的鲁棒性。控制算法应用于分层架构,其中高层和低层控制层分别设计用于间距控制和期望加速度跟踪。由于其灵活的频率特性,提出了一种分数阶控制器,以满足更苛刻的设计要求。寻求等阻尼回路特性,这会产生期望的闭环稳定性,无论受控对象增益如何变化,该稳定性都保持不变。此外,所提出的设计方法的图形化特性证明了其可移植性以及对任何类型车辆动力学的适用性,而无需复杂的重新配置。该算法的优势在频域和时域中得到验证,并且通过在执行自适应巡航控制的真实车辆平台上进行的实验得到验证。