泥浆压力平衡盾构掘进机气室压力调节系统的开发与非线性自适应鲁棒控制

Machines Pub Date : 2024-07-04 DOI:10.3390/machines12070457
Shuai Wang, Yakun Zhang, Guofang Gong, Huayong Yang
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引用次数: 0

摘要

快速准确地控制泥浆压力平衡(SPB)盾构掘进机的气室压力对于建立泥浆压力与土水压力之间的平衡、确保支护面的稳定性至关重要。本文提出了一种基于非线性自适应鲁棒控制(ARC)并使用气动比例三通减压阀的新型气室压力控制方法。首先,开发了气室压力的电动比例控制系统。其次,建立了气室压力调节过程的非线性状态空间模型。利用 SPB 盾构掘进机试验台的实验数据,通过非线性递归最小二乘法算法进行非线性自适应识别。结果证明了模型的有效性和准确性。然后,基于反步法设计了气室压力非线性 ARC,并证明了其 Lyapunov 稳定性。最后,通过仿真和实验验证了本文设计的控制器的可行性和有效性。结果表明,所开发的控制系统可以补偿气室压力调节过程中的非线性和干扰。它能实现良好的瞬态和稳态性能,并对不确定性具有良好的鲁棒性。
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The Development and Nonlinear Adaptive Robust Control of the Air Chamber Pressure Regulation System of a Slurry Pressure Balance Shield Tunneling Machine
The rapid and accurate control of air chamber pressure in slurry pressure balance (SPB) shield tunneling machines is crucial for establishing the balance between slurry pressure and soil and water pressure, ensuring the stability of the support face. A novel air chamber pressure control method based on nonlinear adaptive robust control (ARC) and using a pneumatic proportional three-way pressure-reducing valve is proposed in this paper. Firstly, an electric proportional control system for the air chamber pressure is developed. Secondly, a nonlinear state space model for the air chamber pressure regulation process is established. Utilizing experimental data from the SPB shield tunneling machine test bench, nonlinear adaptive identification is conducted through the nonlinear recursive least square algorithm. The results demonstrate the model’s effectiveness and accuracy. Then, a nonlinear ARC for air chamber pressure is designed based on the backstepping method, and its Lyapunov stability is proved. Finally, the feasibility and effectiveness of the controller designed in this paper is verified through simulation and experiments. The results demonstrate that the developed control system can compensate for the nonlinearity and disturbance in the air chamber pressure regulation process. It can achieve good transient and steady-state performance and has good robustness against uncertainty.
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