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Adaptive Terminal Sliding Mode Control for High-Speed EMU: A MIMO Data-Driven Approach

多输入多输出 控制理论(社会学) 滑模控制 终端(电信) 模式(计算机接口) 计算机科学 自适应控制 控制(管理) 终端滑动模式 控制工程 工程类 电信 物理 频道(广播) 非线性系统 量子力学 人工智能 操作系统
作者
Liang Zhou,Zhongqi Li,Hui Yang,Chang Tan,Yating Fu
出处
期刊:IEEE Transactions on Automation Science and Engineering [Institute of Electrical and Electronics Engineers]
卷期号:: 1-14 被引量:3
标识
DOI:10.1109/tase.2024.3373037
摘要

In this study, a novel data-driven discrete-time sliding mode control (DSMC) approach is designed for an electric multiple unit (EMU) velocity tracking control system. First, the input/output (I/O) data of the EMU are equivalently modeled as a full-format dynamic linearized (FFDL) data model to facilitate the generation of a data-driven control scheme. Subsequently, a discrete terminal sliding mode function and a new hyperbolic reaching-law are introduced to simultaneously achieve fast convergence and alleviate chattering. Based on the designed sliding mode function and reaching-law, an improved discrete-time terminal sliding mode control (iDTSMC) approach is derived using the FFDL model. The proposed approach considers the error feedback, parameter estimation errors, and total uncertainties for compensation, to achieve better control performance. The key advantages of this approach include its sole utilization of input-output data from the EMU system, low controller order, robust parameter adaptability, and anti-interference capabilities. After providing the stability analysis of the proposed method, the iDTSMC scheme is compared and tested on a simulated CRH380A high-speed train experimental platform in a laboratory. The simulation results show that the velocity tracking errors of each power unit of the EMU under the proposed control scheme are within $-$ 0.112 km/h, 0.118 km/h, and the control forces and accelerations are within $-$ 51 kN, 43 kN and $-$ 0.952 m/s $^2$ , 0.827 m/s $^2$ , respectively, with stable fluctuations. Comparative experimental results demonstrate the effectiveness and superiority of the proposed strategy, which remains robust in the presence of disturbances. Note to Practitioners —This study is inspired by the problem of EMU operation control, however, it is also applicable to other systems with trajectory tracking characteristics. Existing automatic train driving control methods are usually based on a dynamics model of the train, which is easily affected by the external environment. In this study, a new data-driven control method is proposed. A discrete terminal sliding mode control function and a new hyperbolic reaching-law were designed based on a dynamic linearized data model equivalent to the EMU operation process. In contrast to similar existing works, the control scheme does not require an accurate EMU dynamic model and is easy to implement. Preliminary simulation experiments show that the method is feasible, however, it has not been incorporated into the train's physical system, nor has it been tested in production. In future research, we plan to promote a combination of control theory and manufacturing practices.
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