$\mathcal {H}_{2}$ Optimal Sliding Hyperplane Design of Discrete-Time Integral Sliding-Mode Control for Automated Driving Vehicles

IF 9.9 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Jin Sung Kim;Chung Choo Chung
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引用次数: 0

Abstract

This article proposes the optimal discrete-time integral sliding-mode control for unmatched external signal compensation in a lane-keeping system on curved roads. Since curved roads appear as an external signal in a lateral vehicle motion model, improving the tracking performance with external signal compensation is necessary. To tackle the problem, we solve the optimization problem of obtaining the optimal sliding surface that minimizes the $\mathcal {H}_{2}$ norm of the transfer matrix from the external signal to the system state of interest. As a result, robust performance in the sense of $\mathcal {H}_{2}$ is guaranteed in the proposed framework. We provide a theorem to prove the $\mathcal {H}_{2}$ performance and present the design process. The proposed method is applied to lateral vehicle control to validate the effectiveness via numerical simulation and real-world experiments. A comparative study confirmed that the tracking performance of the proposed algorithm outperforms those of other methods on curved roads.
自动驾驶车辆离散积分滑模控制的最优滑模超平面设计
本文提出了一种最优离散时间积分滑模控制方法,用于弯曲道路车道保持系统的不匹配外部信号补偿。由于弯道在车辆横向运动模型中是一个外部信号,因此有必要通过外部信号补偿来提高跟踪性能。为了解决这个问题,我们解决了获取从外部信号到系统感兴趣状态的传输矩阵的$\mathcal {H}_{2}$范数最小的最优滑动面的优化问题。因此,所提出的框架保证了$\mathcal {H}_{2}$意义上的鲁棒性能。我们提供了一个定理来证明$\mathcal {H}_{2}$的性能,并给出了设计过程。将该方法应用于车辆横向控制,通过数值仿真和实际试验验证了该方法的有效性。对比研究表明,该算法在弯曲道路上的跟踪性能优于其他方法。
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来源期刊
IEEE Transactions on Industrial Informatics
IEEE Transactions on Industrial Informatics 工程技术-工程:工业
CiteScore
24.10
自引率
8.90%
发文量
1202
审稿时长
5.1 months
期刊介绍: The IEEE Transactions on Industrial Informatics is a multidisciplinary journal dedicated to publishing technical papers that connect theory with practical applications of informatics in industrial settings. It focuses on the utilization of information in intelligent, distributed, and agile industrial automation and control systems. The scope includes topics such as knowledge-based and AI-enhanced automation, intelligent computer control systems, flexible and collaborative manufacturing, industrial informatics in software-defined vehicles and robotics, computer vision, industrial cyber-physical and industrial IoT systems, real-time and networked embedded systems, security in industrial processes, industrial communications, systems interoperability, and human-machine interaction.
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