Optimization of Adaptive Cruise Control system Controller: using Linear Quadratic Gaussian based on Genetic Algorithm
Abstract
In this paper, we propose a novel linear quadratic Gaussian controller whose parameters can be automatically tuned. While linear quadratic regulator method has been widely used in adaptive cruise control system design, researchers have not yet proposed a feasible and effective linear quadratic regulator. Neither did they well tackle with process and measurement noise, nor did they solve the tedious and inefficient tuning problem in adaptive cruise control system design. To compensate for the noise, the authors introduced linear quadratic Gaussian where Kalman filter is applied. And to make the tuning process more efficient, genetic algorithm is used to search for the optimal linear quadratic Gaussian parameters.
Cite
@article{arxiv.1911.08349,
title = {Optimization of Adaptive Cruise Control system Controller: using Linear Quadratic Gaussian based on Genetic Algorithm},
author = {Yuncheng Jiang and Lilong Cai and Xiaofeng Jin},
journal= {arXiv preprint arXiv:1911.08349},
year = {2020}
}
Comments
This paper only introduces the calculation results of application of PID, MPC, and LQD with GA. The technical new matters, contribution to education can not be found .it also proposes a tuning method for LQR's cost function. This concept has already been proposed. Kalman filter is also popular strategy. The novelty of this paper is not sufficiently indicated