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Global Asymptotic Stabilization Using Adaptive Fuzzy PD Control

机译:自适应模糊PD控制的全局渐近稳定

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It is well-known that standard adaptive fuzzy control (AFC) can only guarantee uniformly ultimately bounded stability due to inherent fuzzy approximation errors (FAEs). This paper proves that standard AFC with proportional-derivative (PD) control can guarantee global asymptotic stabilization even in the presence of FAEs for a class of uncertain affine nonlinear systems. Variable-gain PD control is designed to globally stabilize the plant. An optimal FAE is shown to be bounded by the norm of the plant state vector multiplied by a globally invertible and nondecreasing function, which provides a pivotal property for stability analysis. Without discontinuous control compensation, the closed-loop system achieves global and partially asymptotic stability in the sense that all plant states converge to zero. Compared with previous adaptive approximation-based global/asymptotic stabilization approaches, the major advantage of our approach is that global stability and asymptotic stabilization are achieved concurrently by a much simpler control law. Illustrative examples have further verified the theoretical results.
机译:众所周知,由于固有的模糊近似误差(FAE),标准自适应模糊控制(AFC)只能保证统一的最终有界稳定性。本文证明,即使存在一类不确定仿射非线性系统的FAE,具有比例微分(PD)控制的标准AFC仍可保证全局渐近稳定。可变增益PD控制旨在使工厂全局稳定。最佳FAE显示为以植物状态向量的范数乘以全局可逆且不可减少的函数为界,这为稳定性分析提供了关键性。在没有不连续控制补偿的情况下,闭环系统在所有工厂状态都收敛为零的意义上实现了全局和部分渐近稳定性。与以前的基于自适应逼近的全局/渐近稳定方法相比,我们方法的主要优势在于,通过更简单的控制律可以同时实现全局稳定和渐近稳定。说明性实例进一步验证了理论结果。

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