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Dynamic predictor-based adaptive cruise control
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AI
DOI：10.1016/j.jfranklin.2022.06.006.png)
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Abstract
En 中文
We study the stabilization problem of a platoon of Adaptive Cruise Control (ACC) vehicles in the presence of input-delay. We use a dynamic predictor for input-delay compensation, a filtered version of the standard finite spectrum assignment method that overcomes robustness issues, in particular those raised by the approximation of distributed time-delay terms. Each vehicle must achieve the velocity of the preceding vehicle while ensuring a safe inter-vehicular distance established by a time headway-based spacing policy. To this end, a proportional-integral type controller combined with a dynamic predictor is added to each vehicle in the platoon that guarantees stability and zero steady-state error. String stability property of the closed-loop system, i.e., the platoon's ability to attenuate fluctuations arising in the motion of the leading vehicle, is analyzed using a frequency domain framework. The effectiveness of the proposed control scheme is illustrated with simulation results of a platoon of five vehicles. (C) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Keywords:
FINITE SPECTRUM ASSIGNMENT
STRING STABILITY
LINEAR-SYSTEMS
POLICY
FLOW
Journal
J
IF:
3.7
Papers:
6.3K
Citations:
1.5W
