Optimal Direct Yaw Control for Sport Utility Vehicle Using PSO

Mohd Firdaus Omar, I. M. Saadon, R. Ghazali, M. Aripin, C. C. Soon
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引用次数: 1

Abstract

Nowadays the Sport Utility Vehicle (SUV) become more popular than sedan car around the world even in Malaysia. But, these types of vehicles have weaknesses such as higher center of gravity, heavier, side area and wheel base are larger than sedan car that lead to unstable vehicle handling during critical maneuver. Numerous researchers have proposed their control strategy in order to overcome this problem. However, there are less studies about the Linear Quadratic Integral (LQI) controller especially in the Direct Yaw Control (DYC) system. Therefore, in this paper, the development of the LQI controllers implemented in the DYC is researched and compared with Linear Quadratic Regulator (LQR) and Proportional-Integral-Derivative (PID) controller for the performances evaluation. Each controller optimized using Particle Swarm Optimization (PSO) algorithm and tested on lane change maneuver with interference of external disturbance and different road condition. With the help of PSO algorithm, the LQI controllers not only produce significant improvement in the lane change maneuver but the controller is more precise, faster tuning gains, robust against external disturbance and capable to endurance the maneuver with lower Root Mean Square Error (RMSE) compare with two other controllers.
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基于粒子群算法的运动型多功能车直接偏航控制
如今,运动型多用途车(SUV)在世界范围内甚至在马来西亚都比轿车更受欢迎。但与轿车相比,这类车辆具有重心高、重量大、侧边面积大、轴距大等缺点,导致车辆在关键机动时操控不稳定。为了克服这个问题,许多研究者提出了他们的控制策略。然而,对于线性二次积分(LQI)控制器的研究较少,特别是在直接偏航控制(DYC)系统中。因此,本文研究了在DYC中实现的LQI控制器的发展,并将其与线性二次型调节器(LQR)和比例积分导数(PID)控制器进行了性能评价。采用粒子群优化算法对各控制器进行优化,并在外部干扰和不同路况干扰下进行变道机动测试。采用粒子群算法的LQI控制器不仅在变道机动方面取得了显著的改进,而且与其他两种控制器相比,该控制器具有更高的精度、更快的调谐增益、对外界干扰的鲁棒性和更低的均方根误差(RMSE)。
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