Open AccessRobust control of vehicle multi‐target adaptive cruise based on model prediction
Author(s) -
Zhou Zibao,
Zhu Juping,
Li Yuansheng
Publication year - 2020
Publication title -
cognitive computation and systems
Language(s) - English
Resource type - Journals
ISSN - 2517-7567
DOI - 10.1049/ccs.2020.0030
Subject(s) - cruise control , robustness (evolution) , computer science , control theory (sociology) , model predictive control , adaptability , cruise , adaptive control , constraint (computer aided design) , quadratic programming , acceleration , mathematical optimization , control (management) , control engineering , engineering , mathematics , artificial intelligence , aerospace engineering , mechanical engineering , ecology , biochemistry , chemistry , physics , classical mechanics , biology , gene
On the issue of low utilisation and acceptance of current adaptive cruise control (ACC), a multi‐objective adaptive cruise control (MO‐ACC) algorithm is developed in this study. Based on model predictive control theory, comprehensively considering the coordination among various conflicting objectives, the decision of desired longitudinal acceleration is transformed into online quadratic programming (QP) problem. In order to compensate for prediction error caused by modelling mismatch, the robustness of control system is improved by introducing an error feedback correction mechanism. Meanwhile, vector management method is adopted to deal with the non‐feasible solution owing to hard constraints during the process of optimisation. Further, under different work conditions, the focusing performance index along with constraint space varies, and therefore different ACC modes are established to meet the demand of skilled driving groups by means of slightly adjusting performance index, constraint space as well as slack relaxation. The simulations show that under the combined work conditions of the preceding vehicle, the following vehicle can realise seamless switching among various working modes, and also is able to achieve the good expectation during vehicle following, which will help to enhance the adaptability of the ACC system to the complex road traffic environment.