Prescribed Performance-Based Switching Tracking Algorithm for DC–DC Buck Power Converter With Nonaffine Input and Stochastic Disturbance
针对DC-DC降压变换器在负载变化时的输出电压跟踪问题，提出一种有限时间模糊预设性能切换跟踪算法，利用坐标变换和模糊逻辑系统处理非仿射输入和随机扰动，确保跟踪误差收敛到预设小邻域。
This article explores the tracking issue for dc-dc buck power converter with stochastic disturbance, specifically focusing on how output voltage tracks to a desired voltage in a finite-time when the load changes. Meanwhile, considering unmodeled dynamics and nonaffine inputs, we propose an innovative finite-time fuzzy prescribed performance switching tracking algorithm to achieve tracking goal. For realizing the requirements of performance, the algorithm converts the tracking error to a new state by means of a coordinate transformation via the tangent function. In addition, the universal approximation capacity of the fuzzy-logic system is utilized to estimate the unknown nonlinear term effectively. On this basis, the designed adaptive dynamic event-triggered controller can not only ensure that all the signals for the closed-loop system remain bounded in probability but also guarantee that the tracking error will converge to a predetermined small neighborhood. Meanwhile, different piecewise functions are added into the controller to characterize prescribed performance and avoid singularity problems, respectively. Finally, the effectiveness of the tracking control algorithm is fully demonstrated by the simulations of the dc-dc buck power converter.