Off-road distributed-drive electric vehicle trajectory tracking control with constrained Transformer MPC

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice Pub Date : 2025-10-18 DOI:10.1016/j.conengprac.2025.106608

Fawang Zhang , Sichao Wu , Yimiao Zhang , Hui Liu , Shida Nie , Jingliang Duan , Rui Liu , Changle Xiang

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引用次数: 0

Abstract

Trajectory tracking control for off-road distributed-drive electric vehicles presents significant challenges due to compound slope effects and rollover risks. Existing approaches often neglect the critical impact of coupled slopes on vehicle roll dynamics and face substantial computational burdens during real-time implementation. This paper presents a four-degree-of-freedom vehicle dynamic model that comprehensively captures longitudinal, lateral, yaw, and roll motions while accounting for compound grade effects. We propose a novel Constrained Transformer Model Predictive Control algorithm that enables real-time policy computation while maintaining safety constraints. CarSim co-simulations demonstrate that our approach effectively prevents rollover and improves trajectory tracking accuracy by 72.28% across various off-road scenarios while reducing computational complexity by 213 times compared to conventional online optimization MPC. Real vehicle tests in off-road environments further validate the effectiveness of the proposed algorithm.

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基于约束变压器MPC的越野分布式驱动电动汽车轨迹跟踪控制

由于复杂的斜坡效应和侧翻风险，越野分布式驱动电动汽车的轨迹跟踪控制面临着巨大的挑战。现有的方法往往忽略了耦合坡度对车辆侧倾动力学的关键影响，并且在实时实现过程中面临着巨大的计算负担。本文提出了一个四自由度的车辆动态模型，全面捕捉纵向，横向，偏航和滚动运动，同时考虑复合等级效应。我们提出了一种新的约束变压器模型预测控制算法，在保持安全约束的同时实现实时策略计算。CarSim联合仿真表明，与传统的在线优化MPC相比，我们的方法有效地防止了侧翻，并在各种越野场景下将轨迹跟踪精度提高了72.28%，同时将计算复杂度降低了213倍。非道路环境下的实车试验进一步验证了算法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Control Engineering Practice 工程技术-工程：电子与电气

CiteScore

9.20

自引率

12.20%

发文量

183

审稿时长

44 days

期刊介绍： Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice''s sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper. The scope of Control Engineering Practice matches the activities of IFAC. Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome.