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Quantum particle swarm optimisation algorithm for feedback control of semi-autonomous driver assistance systems

机译:半自动驾驶辅助系统反馈控制的量子粒子群算法

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摘要

The development of automotive technology has become increasingly important for preventing car accidents. Hence, as a basic research of driver assistance systems, a novel control method has been proposed for steering support. In particular, the stability and limitation of such a system is investigated for the safe and comfortable drive. First, the particle swarm optimisation (PSO)-based algorithm is used to search the optimal feedback gain under practical constraints for achieving tracking control. Moreover, to reduce the convergence time further, the PSO algorithm is combined with the technique of quantum computing. Simulation results indicate that the proposed feedback controller based on quantum PSO has the ability to provide efficient computational performance for trajectory tracking and stabilisation.
机译:汽车技术的发展对于预防交通事故已变得越来越重要。因此,作为驾驶员辅助系统的基础研究,提出了一种新颖的转向辅助控制方法。特别地,为了安全和舒适的驾驶,研究了这种系统的稳定性和局限性。首先,基于粒子群优化(PSO)的算法用于在实际约束下搜索最优反馈增益,以实现跟踪控制。此外,为了进一步减少收敛时间,PSO算法与量子计算技术相结合。仿真结果表明,所提出的基于量子粒子群优化算法的反馈控制器能够为轨迹跟踪和稳定化提供有效的计算性能。

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