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Longitudinal control of an intelligent vehicle using particle swarm optimization based sliding mode control

机译:基于粒子群优化的滑模控制智能汽车纵向控制

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摘要

This paper focuses on the design of longitudinal controller for an intelligent vehicle which was built at Asian Institute of Technology based on sliding mode control. The proposed controller uses particle swarm optimization (PSO) for optimal tuning of sliding surface and controller gain in the sliding mode controller (SMC). The longitudinal control is conducted via controlling of throttle value angle using PSO-based SMC on the simplified first-order linear model of the intelligent vehicle and controlling of brake force using fuzzy logic. In order to achieve the desired headway time, integration of throttle valve angle control and brake force control is required. To obtain the optimal parameters of SMC, two equations velocity updating and position updating are applied. Firstly, the performance of proposed controller is evaluated by using MATLAB simulation to compare with conventional PD controller. Finally, the experimental results show that the proposed PSO-based SMC can perform efficiently in longitudinal control of the intelligent vehicle.
机译:本文重点研究了亚洲理工学院基于滑模控制构建的智能汽车纵向控制器设计。所提出的控制器使用粒子群优化(PSO)对滑动模式控制器(SMC)中的滑动表面和控制器增益进行优化调整。纵向控制是通过在简化的智能汽车一阶线性模型上使用基于PSO的SMC控制节气门值角度和使用模糊逻辑控制制动力来实现的。为了达到所需的行驶时间,需要集成节气门角度控制和制动力控制。为了获得SMC的最优参数,应用了速度更新和位置更新两个方程。首先,利用MATLAB仿真与传统PD控制器的比较,对所提控制器的性能进行了评估;最后,实验结果表明,所提出的基于PSO的SMC能够有效地进行智能汽车的纵向控制。

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