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Globally stable direct fuzzy model reference adaptive control

机译：全局稳定直接模糊模型参考自适应控制

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摘要

In the paper a fuzzy adaptive control algorithm is presented. It belongs to the class of direct model reference adaptive techniques based on a fuzzy (Takagi-Sugeno) model of the plant. The plant to be controlled is assumed to be nonlinear and predominantly of the first order. Consequently, the resulting adaptive and control laws are very simple and thus interesting for use in practical applications. The system remains stable in the presence of unmodelled dynamics (disturbances, parasitic high-order dynamics and reconstruction errors are treated explicitly). The global stability of the overall system is proven in the paper, i.e. it is shown that all signals remain bounded while the tracking error and estimated parameters converge to some residual set that depends on the size of disturbance and high-order parasitic dynamics. The proposed algorithm is tested on a simulated three-tank system. Its performance is compared to the performance of a classical MRAC.
机译：本文提出了一种模糊自适应控制算法。它属于基于植物的模糊（Takagi-Sugeno）模型的直接模型参考自适应技术的类别。假定要控制的设备是非线性的，并且主要是一阶的。因此，所得的自适应律和控制律非常简单，因此在实际应用中很有用。在存在未建模的动力学的情况下，系统保持稳定（对干扰，寄生高阶动力学和重构错误进行了明确处理）。该论文证明了整个系统的全局稳定性，即表明所有信号都保持有界，而跟踪误差和估计参数收敛到某个残差集，这取决于扰动和高阶寄生动力学的大小。该算法在模拟的三缸系统上进行了测试。将其性能与经典MRAC的性能进行比较。

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