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An active disturbance rejection controller for a parallel Robot via Generalized Proportional Integral observers

机译:通过广义比例积分观测器为并联机器人提供主动干扰抑制控制器

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In this article, we address an active disturbance rejection controller design for the output reference trajectory tracking problem in a 3 degree of freedom (DOF) Delta Robot. The proposed method relies on purely linear high gain disturbance observation and linear feedback control techniques. The estimation tasks are carried out with the help of Generalized Proportional Integral (GPI) observers, endowed with output integral injection to counteract zero mean measurement noise effects. As the lumped exogenous and endogenous disturbance inputs are estimated, the observers deliver them to the controllers for on-line disturbance cancelation, while simultaneously the phase variables, related to the measured flat outputs, are being estimated by the same GPI observer. The gathered values of the phase variables are used to complete a linear multivariable output feedback control scheme. The proposed control scheme avoids the traditional computed torque method, reducing the computation time and bypassing the need for explicit, accurate, knowledge of the plant. The estimation and control method is only approximate as small as desired reconstruction, or tracking, errors are guaranteed. The reported results, including laboratory experiments, are significantly better than the results provided by the classical model-based techniques, when the system is subject to endogenous and exogenous uncertainties.
机译:在本文中,我们针对3自由度(DOF)Delta机器人中的输出参考轨迹跟踪问题解决了有源干扰抑制控制器的设计。该方法基于纯线性高增益干扰观测和线性反馈控制技术。估计任务是在广义比例积分(GPI)观测器的帮助下执行的,这些观测器具有输出积分注入以抵消零平均测量噪声的影响。由于估计了总的外源性和内源性干扰输入,观察者将它们传送到控制器以进行在线干扰消除,同时,同一GPI观察者正在估计与测得的平面输出有关的相位变量。相位变量的收集值用于完成线性多变量输出反馈控制方案。所提出的控制方案避免了传统的计算转矩方法,从而减少了计算时间,并且绕过了对显式,准确的工厂知识的需求。估计和控制方法仅与所需的重建或跟踪误差一样小。当系统受到内源性和外源性不确定性的影响时,包括实验室实验在内的报告结果明显优于基于经典模型的技术所提供的结果。

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