具有不确定性的隧道掘进机刀盘伸缩系统的自适应滑模控制

IF 1.9 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Industrial Robot-The International Journal of Robotics Research and Application Pub Date : 2022-08-25 DOI:10.1108/ir-04-2022-0096
Hangjun Zhang, Jin-hui Fang, Jianhua Wei, Huan Yu, Qiang Zhang
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引用次数: 0

摘要

目的提出一种具有不确定性的隧道掘进机刀盘伸缩系统的自适应滑模控制(ASMC),以实现复杂地层中的高精度轨迹。该方法可用于求解由线性和非线性模型不确定性引起的问题。设计/方法/方法首先,定义了一个积分型滑动面来减小静态跟踪误差。其次,设计了一种投影型自适应律来逼近电液系统的线性和非线性重定义参数。第三,提出了一种具有连续逼近函数的非线性鲁棒项,用于处理负载力不确定性和减小滑模抖振。利用李雅普诺夫理论保证了闭环系统的稳定性。最后,通过实验验证了该控制器的有效性。发现线性和非线性模型的不确定性导致机构动力学和跟踪误差的大变化。为了实现精确的位置跟踪,在滑模控制中引入自适应律来补偿模型的不确定性。采用连续逼近函数减小固有滑模抖振,采用非线性鲁棒反馈解决负载力的不确定性。因此,针对具有不确定性的隧道掘进机刀盘伸缩系统,提出了一种新型ASMC,可以提高其跟踪精度,减少滑模抖振。据作者所知,首次提出了一种具有不确定性的隧道掘进机刀盘伸缩系统控制方法。所提出的控制方法不仅在控制精度上有效,而且在参数不确定度上也有效。
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Adaptive sliding mode control for tunnel boring machine cutterhead telescopic system with uncertainties
Purpose This paper aims to present an adaptive sliding mode control (ASMC) for tunnel boring machine cutterhead telescopic system with uncertainties to achieve a high-precision trajectory in complex strata. This method could be applied to solve the problems caused by linear and nonlinear model uncertainties. Design/methodology/approach First, an integral-type sliding surface is defined to reduce the static tracking error. Second, a projection type adaptation law is designed to approximate the linear and nonlinear redefined parameters of the electrohydraulic system. Third, a nonlinear robust term with a continuous approximation function is presented for handling load force uncertainty and reducing sliding mode chattering. Moreover, Lyapunov theory is applied to guarantee the stability of the closed-loop system. Finally, the effectiveness of the proposed controller is proved by comparative experiments on a scaled test rig. Findings The linear and nonlinear model uncertainties lead to large variations in the dynamics of the mechanism and the tracking error. To achieve precise position tracking, an adaptation law was integrated into the sliding mode control which compensated for model uncertainties. Besides, the inherent sliding mode chattering was reduced by a continuous approximation function, while load force uncertainty was solved by a nonlinear robust feedback. Therefore, a novel ASMC for tunnel boring machine cutterhead telescopic system with uncertainties can improve its tracking precision and reduce the sliding mode chattering. Originality/value To the best of the authors’ knowledge, the ASMC is proposed for the first time to control the tunnel boring machine cutterhead telescopic system with uncertainties. The presented control is effective not only in control accuracy but also in parameter uncertainty.
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来源期刊
CiteScore
4.50
自引率
16.70%
发文量
86
审稿时长
5.7 months
期刊介绍: Industrial Robot publishes peer reviewed research articles, technology reviews and specially commissioned case studies. Each issue includes high quality content covering all aspects of robotic technology, and reflecting the most interesting and strategically important research and development activities from around the world. The journal’s policy of not publishing work that has only been tested in simulation means that only the very best and most practical research articles are included. This ensures that the material that is published has real relevance and value for commercial manufacturing and research organizations. Industrial Robot''s coverage includes, but is not restricted to: Automatic assembly Flexible manufacturing Programming optimisation Simulation and offline programming Service robots Autonomous robots Swarm intelligence Humanoid robots Prosthetics and exoskeletons Machine intelligence Military robots Underwater and aerial robots Cooperative robots Flexible grippers and tactile sensing Robot vision Teleoperation Mobile robots Search and rescue robots Robot welding Collision avoidance Robotic machining Surgical robots Call for Papers 2020 AI for Autonomous Unmanned Systems Agricultural Robot Brain-Computer Interfaces for Human-Robot Interaction Cooperative Robots Robots for Environmental Monitoring Rehabilitation Robots Wearable Robotics/Exoskeletons.
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