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Adaptive Fuzzy Hierarchical Sliding-Mode Control for the Trajectory Tracking of Uncertain Underactuated Nonlinear Dynamic Systems

机译:不确定欠驱动非线性动力系统轨迹跟踪的自适应模糊层次滑模控制

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摘要

The trajectory tracking of uncertain underactuated nonlinear dynamic systems is tackled by an adaptive fuzzy hierarchical sliding-mode control (AFHSMC). First, one of the subsystems is assigned as the first layer sliding surface. Next, a second layer sliding surface from the first layer sliding surface and the sliding surface of another subsystem is constructed. In this paper, the $n$th layer is supposed to be the top layer (or hierarchical layer) for including the sliding surfaces of all subsystems. Because two nonlinear system functions and the time-varying external disturbance of each subsystem are supposed to be unknown, different online fuzzy models are employed to approximate these nonlinear system functions and the upper bounded functions of external disturbances. Moreover, the upper bound of uncertainties caused by these fuzzy modeling errors is estimated online. Based on these learning fuzzy models and the estimated upper bound of these modeling errors, an AFHSMC is developed. The stability analysis and tracking performance of the closed-loop system are verified by Lyapunov stability theory. Finally, two simulation examples including different amplitudes of external disturbance and comparison with hierarchical sliding-mode control confirm the effectiveness and robustness of the proposed control.
机译:不确定的欠驱动非线性动力学系统的轨迹跟踪通过自适应模糊层次滑模控制(AFHSMC)解决。首先,将一个子系统分配为第一层滑动表面。接下来,从第一层滑动表面和另一子系统的滑动表面构造第二层滑动表面。在本文中,第n层应该是包括所有子系统的滑动表面的顶层(或分层层)。由于假设两个子系统的非线性系统函数和时变外部扰动是未知的,因此采用不同的在线模糊模型来近似这些非线性系统函数和外部扰动的上限函数。此外,可以在线估算由这些模糊建模误差引起的不确定性的上限。基于这些学习模糊模型和这些建模误差的估计上限,开发了一种AFHSMC。利用Lyapunov稳定性理论验证了闭环系统的稳定性分析和跟踪性能。最后,两个仿真示例包括不同的外部干扰幅度以及与分层滑模控制的比较,证实了所提出控制的有效性和鲁棒性。

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