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首页> 外文期刊>IEEE Transactions on Control Systems Technology >Robust Sliding Mode Control for Robots Driven by Compliant Actuators
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Robust Sliding Mode Control for Robots Driven by Compliant Actuators

机译:兼容执行器驱动的机器人的鲁棒滑模控制

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摘要

Compliant actuators can offer many attractive features over stiff actuators in real human-robot interaction applications, such as low output impedance, smooth force transmission, and shock tolerance. This brief focuses on a robust sliding mode control (SMC) methodology for robotic systems with compliant actuators. First, a continuous SMC design is introduced due to its advantages of strong robustness and chattering attenuation. However, this continuous SMC structure cannot guarantee a high tracking performance in the presence of mismatched disturbances in compliantly actuated robots. Meanwhile, in many application fields, compliantly actuated robots are affected by different kinds of time-varying disturbances, including external environmental disturbances, internal parameter uncertainties, and frictions, which may be in the form of constant, ramp, and parabolic disturbances. To estimate such unknown disturbances, a generalized proportional integral observer (GPIO) technique is employed. By designing a new sliding surface with the help of disturbance estimation, a GPIO-based continuous SMC method is synthesized, which is used to deal with matched/mismatched time-varying disturbances. A detailed stability analysis of the closed-loop system is also presented. Experimental results under three different test conditions are provided to illustrate the promising tracking performance of the proposed control strategy.
机译:在实际的人机交互应用中,兼容的执行器可以提供比刚性执行器更吸引人的功能,例如低输出阻抗,平稳的力传递和耐震性。本摘要重点介绍了用于带有兼容执行器的机器人系统的鲁棒滑模控制(SMC)方法。首先,由于其强大的鲁棒性和颤振衰减的优势,引入了连续SMC设计。但是,这种连续的SMC结构在顺应性驱动的机器人存在失配干扰的情况下不能保证较高的跟踪性能。同时,在许多应用领域中,依从性驱动的机器人会受到各种时变干扰的影响,包括外部环境干扰,内部参数不确定性和摩擦,这些干扰可能以恒定,斜坡和抛物线形式出现。为了估算此类未知干扰,采用了通用比例积分观测器(GPIO)技术。通过借助扰动估计设计新的滑动表面,综合了基于GPIO的连续SMC方法,该方法用于处理匹配/不匹配的时变扰动。还介绍了闭环系统的详细稳定性分析。提供了三种不同测试条件下的实验结果,以说明所提出的控制策略的有希望的跟踪性能。

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