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Adaptive sliding control with self-tuning fuzzy compensation for a piezoelectrically actuated X–Y table

机译:压电致动XY工作台的带有自校正模糊补偿的自适应滑动控制

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摘要

The piezoelectrically actuated system has non-linear and time-varying behaviour, hence it is difficult to establish an accurate dynamic model for a model-based sliding-mode control design. In this study, a model-free adaptive sliding controller is proposed to control the piezoelectrically actuated system. This control strategy uses the functional approximation (FA) technique to establish the unknown function for releasing the model-based requirement of the sliding-mode control. In addition, a fuzzy scheme with online learning ability is introduced to compensate the FA error for improving the control performance and reducing the implementation difficulty. The important advantages of this approach are to achieve the sliding-mode controller design without the system dynamic model requirement and release the trial-and-error work of selecting approximation function. The update laws for the coefficients of the Fourier series functions and the fuzzy tuning parameters are derived from a Lyapunov function to guarantee the control system stability. This proposed controller is implemented on a piezoelectrically actuated X–Y table. To verify the dynamic performance improvement of inducing a fuzzy compensation in this model-free controller, the dynamic responses of the proposed controller are compared with those of the adaptive sliding controller without fuzzy compensation.
机译:压电致动系统具有非线性且随时间变化的行为,因此难以为基于模型的滑模控制设计建立准确的动力学模型。在这项研究中,提出了一种无模型的自适应滑动控制器来控制压电驱动系统。该控制策略使用函数逼近(FA)技术来建立未知函数,以释放基于模型的滑模控制要求。另外,引入具有在线学习能力的模糊方案来补偿FA误差,以提高控制性能并降低实现难度。该方法的重要优点是无需系统动力学模型即可实现滑模控制器设计,并释放了选择逼近函数的反复试验工作。从Lyapunov函数推导傅立叶级数函数的系数和模糊调整参数的更新律,以确保控制系统的稳定性。该建议的控制器在压电驱动的X-Y工作台上实现。为了验证这种无模型控制器中引入模糊补偿的动态性能改进,将所提出的控制器的动态响应与没有模糊补偿的自适应滑动控制器的动态响应进行了比较。

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