| 周正阳,潘树国,蔚保国,高旺,陈宗良.基于ABMSSA的PP算法分布式自动驾驶轨迹跟踪控制策略[J].电子测量与仪器学报,2024,38(6):50-57 |
| 基于ABMSSA的PP算法分布式自动驾驶轨迹跟踪控制策略 |
| Distributed automatic driving trajectory tracking control strategybased on PP algorithm based on ABMSSA |
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| DOI： |
| 中文关键词: 轨迹跟踪 纯追踪控制 双环PID速度控制 改进樽海鞘优化算法 |
| 英文关键词:trajectory tracking pure pursuit control double loop PID speed control improved salpa optimization algorithm |
| 基金项目:国家重点研发计划课题（2021YFB3900804）项目资助 |
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| Author | Institution |
| Zhou Zhengyang | School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China |
| Pan Shuguo | School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China |
| Yu Baoguo | State Key Laboratory of Satellite Navigation System and Equipment Technology, Shijiazhuang 050081, China |
| Gao Wang | School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China |
| Chen Zongliang | School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China |
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| 摘要点击次数: 37 |
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| 中文摘要: |
| 针对在轨迹跟踪控制中横向纯追踪控制算法前视距离的选取受车辆速度影响较大的问题,本文设计了一种改进樽海鞘优化算法对纯追踪控制中的前视距离进行实时调整优化。首先在纯追踪控制模型的基础之上,采用横向误差作为主要决策参数,设计了改进樽海鞘优化算法的目标函数,同时还在算法中引入布朗运动和自适应权重以防止陷入局部最优解和提高算法的收敛速度。其次本文还设计了纵向双环PID控制算法用于实现智能体车辆对于参考速度的跟踪。最后在智能体车辆实际平台上对所提出的基于分布式纵向双环PID控制算法、横向前视距离优化的纯追踪控制算法进行实验验证,并且设置多组对比实验。结果表明采用基于前视距离优化的纯追踪轨迹跟踪控制控制算法具有最优控制性能,其中最大横向误差为0.068 m,平均横向误差为0.014 m,相较于模糊优化其控制精度提升了24.73%。 |
| 英文摘要: |
| Aiming at the problem that the forward looking distance of the lateral pure tracking control algorithm is greatly affected by the vehicle speed, this paper designs an improved Salp optimization algorithm to adjust and optimize the forward looking distance in the pure tracking control in real time. Firstly, based on the pure tracking control model, the objective function of the improved Salp optimization algorithm is designed with the lateral error as the main decision parameter, and Brownian motion and adaptive weights are introduced into the algorithm to prevent falling into the local optimal solution and improve the convergence speed of the algorithm. Secondly, the longitudinal double-loop PID control algorithm is designed to track the reference speed of the vehicle. Finally, the proposed pure tracking control algorithm based on distributed longitudinal double-loop PID control algorithm and lateral forward distance optimization is verified experimentally on the actual platform of the agent vehicle, and multiple groups of comparison experiments are set up. The results show that the pure tracking trajectory tracking control algorithm based on forward looking distance optimization has the best control performance, in which the maximum lateral error is 0.068 m and the average lateral error is 0.014 m, and the control accuracy is improved by 24.73% compared with fuzzy optimization. |
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