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Optimal Direct Yaw Control for Sport Utility Vehicle Using PSO

机译:使用PSO的运​​动型多功能车辆的最佳直接偏航控制

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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.
机译:如今,即使在马来西亚,也比世界各地的轿车汽车更受欢迎的运动型电脑(SUV)。但是,这些类型的车辆具有较高的重心,较重,侧面和轮基的劣势,比轿车汽车更大,导致在临界操作期间的不稳定车辆处理。许多研究人员提出了他们的控制策略,以克服这个问题。然而,关于线性二次积分(LQI)控制器的研究尤其在直接偏航控制(DYC)系统中。因此,在本文中,研究了在DYC中实现的LQI控制器的发展,并与用于性能评估的线性二次调节器(LQR)和比例 - 积分 - 衍生(PID)控制器进行比较。每个控制器都使用粒子群优化(PSO)算法进行了优化,并在车道变换机动上进行了干扰,具有外部干扰和不同的道路状况。在PSO算法的帮助下,LQI控制器不仅在车道变换机动方面产生了显着的改进,而且控制器更加精确,更快的调整增益,鲁棒抵抗外部干扰,能够耐动地具有较低根均方误差的机动(RMSE)与其他两个控制器比较。

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