加权
拖车
控制理论(社会学)
线性二次调节器
控制器(灌溉)
理论(学习稳定性)
控制工程
计算机科学
工程类
遗传算法
最优控制
控制(管理)
汽车工程
数学
数学优化
人工智能
机器学习
放射科
生物
医学
农学
标识
DOI:10.1115/imece2014-36477
摘要
To date, Linear Quadratic Regulator (LQR) controllers based on linear vehicle models have been researched and developed for improving the lateral stability of car-trailer (CT) combinations. However, in the LQR controller design, there is no a systematic way to determine the weighting factors of the performance index. Generally, the weighting factors are selected using trial and error based on designer’s experience. In order to facilitate the LQR controller design, a new method based on a genetic algorithm (GA) is presented to determine the appropriate weighting factors in the LQR controller design. To examine the proposed method, a controller for an active trailer differential braking (ATDB) system of a car-trailer (CT) system is designed and examined. The simulation results indicate that compared with the LQR controller based on the weighting factors derived from the conventional trial and error method, the controller developed using the proposed method exhibits better performance.
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