Practical Adaptive Fuzzy Control of Nonlinear Pure-Feedback Systems With Quantized Nonlinearity Input
针对一类输入信号被量化的非线性纯反馈系统，提出了一种模糊自适应控制方法，通过反步法设计控制器，确保闭环信号有界且跟踪误差满足预设精度，并用仿真验证了有效性。
This paper investigates the fuzzy adaptive practical tracking problem for a class of nonlinear pure-feedback systems with quantized input signal. In the control scheme design process, the considered system is transformed into a plant with a strict-feedback form by borrowing the mean value theorem of differential, then fuzzy logic systems are used to compensate for some uncertain nonlinearities in the considered plant and the classical adaptive technique is employed to handle some unknown parameters. In the backstepping design, some nonnegative switching functions are introduced to develop the desired fuzzy controller, and Barbalat's lemma is used to analyze the stability and the control performance of the closed-loop system. It can be shown that under the novel adaptive fuzzy controller, all the closed-loop signals are semiglobally uniformly ultimately bounded, and especially the tracking error satisfies the accuracy assigned a priori. A simulation example is presented to verify the effectiveness of the proposed control method.