控制(管理)
自适应控制
控制理论(社会学)
功率(物理)
计算机科学
控制工程
工程类
人工智能
物理
量子力学
作者
Xiangwei Rong,Dehua Shi,Shaohua Wang,Chunfang Yin,Chun Li
标识
DOI:10.1177/09544062251353424
摘要
To address the issue of control redundancy and the limited adaptability of the dynamic coordination control strategy (DCCS) during mode transition in compound power-split hybrid vehicles (CPS-HEVs), the paper proposes a control allocation-based adaptive dynamic coordinated control strategy (CABA-DCCS). The proposed method integrates an H ∞ robust controller with an adaptive control allocator. Specifically, an H ∞ state feedback controller is designed using the angular velocity and its integral tracking error as control inputs, resulting in a virtual control law with guaranteed robustness. Subsequently, a control allocator is constructed to minimize control efforts, where the allocation weight coefficients are dynamically tuned via a fuzzy controller that takes acceleration error and speed error as inputs. (While the individual components may not represent entirely novel contributions to control theory, their integration and application to this specific challenge distinguish the proposed strategy from existing methods.) Finally, the strategy is validated through both simulation and hardware-in-the-loop (HiL) testing. Results show that the proposed control approach consistently limits the longitudinal impact of CPS-HEVs to below 10 m/s 3 under different acceleration conditions, significantly enhancing the adaptability of mode transition technology.
科研通智能强力驱动
Strongly Powered by AbleSci AI