反推
控制理论(社会学)
计算机科学
非线性系统
控制器(灌溉)
跟踪误差
补偿(心理学)
瞬态(计算机编程)
过程(计算)
趋同(经济学)
控制工程
理论(学习稳定性)
伺服机构
跟踪(教育)
伺服
自适应控制
控制(管理)
工程类
人工智能
心理学
教育学
物理
量子力学
机器学习
精神分析
农学
经济
生物
经济增长
操作系统
作者
Yu Wan,Wen Long Yue,Xuehui Gao,Qiang Chen,Roger Xu
标识
DOI:10.1016/j.neucom.2023.126967
摘要
Hydraulic systems present numerous challenges in the development of high-performance tracking controllers due to their highly nonlinear characteristics and heavy modeling uncertainties. Addressing this issue, this paper presents a friction compensation-based finite-time tracking control strategy with prescribed performance constraints. The system model is first derived, taking into consideration the nonlinear behaviors and potential uncertainties encountered in practical scenarios. Then, an adaptive finite-time prescribed performance controller is synthesized based on the backstepping framework. A novel form of finite-time performance function is introduced to constrain the tracking error, which provides the closed-loop system with a less complex guarantee of finite-time convergence and can also deliver the required transient performance and steady-state accuracy. Additionally, given the impact of uncertainty terms and the difficulty in obtaining the virtual command derivative, we employ neural networks (NNs) to estimate unknown dynamics and introduce command filters to acquire the intermediate signals, simplifying the backstepping control design process. Theoretical analysis indicates that the proposed control strategy can achieve the desired tracking performance and ensure the stability of the entire closed-loop system. Comparative numerical simulations are presented to confirm the usefulness of the suggested approach.
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