优化的模糊控制器,提高舒适度在过渡期间的巡航和自适应巡航控制车辆

S. Sathiyan, S. Kumar, A. Selvakumar
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引用次数: 10

摘要

在巡航控制(CC)和自适应巡航控制(ACC)车辆中,采用比例微分(PD)、比例积分(PI)和比例积分微分(PID)等传统控制器实现速度控制模式(VCM)。在CC的“恢复模式”中发生的转换以及在ACC从距离控制模式(DCM)切换到VCM期间发生的转换主要用于控制器的设计。这种转变对车辆乘员的舒适度产生了干扰。超过预定义水平的干扰可能导致用户拒绝这种驾驶员辅助系统。所提出的遗传算法优化模糊控制器在控制加速度在舒适范围内,使制动力矩最小方面优于传统CC系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimised fuzzy controller for improved comfort level during transitions in Cruise and Adaptive Cruise Control Vehicles
Conventional controllers like Proportional Derivative (PD), Proportional Integral (PI) and Proportional Integral Derivative (PID) controllers were used in implementing Velocity Control Mode (VCM) in Cruise Control (CC) and Adaptive Cruise control (ACC) vehicles. Transition that occur in "resume mode" of CC and transitions that occur during switching from Distance Control Mode (DCM) to VCM for an ACC is considered primarily for the design of a controller. This transition creates the disturbance in the comfort level of the vehicle occupants. Disturbance above a predefined level may lead to rejection of such driver assistance systems by the user. The proposed optimized fuzzy controller using Genetic Algorithm (GA) has shown a better performance over the conventional CC system in terms of minimizing the jerk by controlling the acceleration within the comfortable level.
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