Enhancing stability and safety: A novel multi-constraint model predictive control approach for forklift trajectory

IF 1.5 Q3 AUTOMATION & CONTROL SYSTEMS IET Cybersystems and Robotics Pub Date : 2024-12-31 DOI:10.1049/csy2.70004
Yizhen Sun, Junyou Yang, Donghui Zhao, Moses Chukwuka Okonkwo, Jianmin Zhang, Shuoyu Wang, Yang Liu
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Abstract

The advancements in intelligent manufacturing have made high-precision trajectory tracking technology crucial for improving the efficiency and safety of in-factory cargo transportation. This study addresses the limitations of current forklift navigation systems in trajectory control accuracy and stability by proposing the Enhanced Stability and Safety Model Predictive Control (ESS-MPC) method. This approach includes a multi-constraint strategy for improved stability and safety. The kinematic model for a single front steering-wheel forklift vehicle is constructed with all known state quantities, including the steering angle, resulting in a more accurate model description and trajectory prediction. To ensure vehicle safety, the spatial safety boundary obtained from the trajectory planning module is established as a hard constraint for ESS-MPC tracking. The optimisation constraints are also updated with the key kinematic and dynamic parameters of the forklift. The ESS-MPC method improved the position and pose accuracy and stability by 57.93%, 37.83%, and 57.51%, respectively, as demonstrated through experimental validation using simulation and real-world environments. This study provides significant support for the development of autonomous navigation systems for industrial forklifts.

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来源期刊
IET Cybersystems and Robotics
IET Cybersystems and Robotics Computer Science-Information Systems
CiteScore
3.70
自引率
0.00%
发文量
31
审稿时长
34 weeks
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