Buck变换器的改进型互补滑模控制

Improved complementary sliding mode control for Buck converter

中文关键词  Buck变换器  匹配和不匹配干扰  干扰观测器  改进型互补滑模控制  鲁棒性  李雅普诺夫稳定

英文关键词  Buck converter  matched and mismatched disturbances  disturbance observer  improved complementary sliding mode control  robustness  Lyapunov stability

中文摘要

      针对Buck变换器系统中存在匹配和不匹配干扰的问题, 本文提出了一种基于干扰观测器(DOB)的改进型互补滑模控制(CSMC)策略. 首先, 建立存在多重干扰的Buck变换器数学模型, 将模型改写为标准二阶积分型控制对象, 将式中干扰统一为匹配干扰和不匹配干扰. 其次, 设计2个DOB分别估计匹配干扰和不匹配干扰, 实现有限时间内跟踪干扰信号, 以抵消各种不确定性对系统的影响. 然后, 设计互补滑模面, 提出基于等效控制的改进型互补滑模控制律, 保留边界层内鲁棒性的同时, 提升控制器的动态性能, 减小静态误差, 拓宽边界层参数选择范围. 最后, 基于李雅普诺夫理论证明所提出控制器的稳定性. 数字仿真表明, 提出的改进型CSMC控制器结合DOB的总体控制方案能够有效抑制系统匹配和不匹配干扰, 同时获得更快的收敛速度以及更高的跟踪精度.

英文摘要

      An improved complementary sliding mode control(CSMC) strategy based on the disturbance observer (DOB) is proposed in this paper to solve the control problem of Buck converter system with matched and mismatched disturbance. Firstly, the mathematical model of Buck converter with many kinds of disturbance was established, we rewrite it to a standard second-order cascade control system. The lumped disturbance in the formula was combined, separately, as matched and mismatched disturbances. Secondly, two DOBs are designed to estimate the matched and mismatched disturbance respectively in the system equation, which can track the disturbance signal in finite time, so the controller can suppress the influence of various uncertainties in the system. Then, the complementary sliding mode surface is designed and an improved complementary sliding mode reaching law based on the equivalent control is proposed, which preserves the robustness inside the boundary layer, improves the dynamic performance of the controller, reduces the static error, and broadens the selection range of boundary layer parameter. Finally, the stability of the controller is proved based on the Lyapunov theory. Digital simulation shows that the proposed improved CSMC controller combined with DOB can effectively suppress the matched and mismatched disturbance, achieve a faster convergence rate and higher tracking accuracy.