非严格重复逆变器系统自抗扰学习控制

Active disturbance rejection learning control for inverter systems with non-repetitive features

中文关键词  数据驱动  迭代学习控制  扩张状态观测器  逆变器  非严格重复

英文关键词  data-driven  iterative learning control  extended state observer  inverter  non-repetitiveness

中文摘要

      控制器中, 误差是生成控制量的主要信息来源, 其所含信息质量直接决定当前时刻的控制效果. 本文利用 误差有效值来反映周期误差能量的变化, 通过设定其变化强度阈值对非严格重复信息进行选择和剔除, 从而提高学 习控制的信息品质. 将学习控制简化为仅含有一个2N阶滤波器的单位正反馈环节, 通过分析学习控制周期收敛条 件, 并结合逆变系统运行基波以及各次谐波频带, 给出了滤波器截止频率的确定方法. 抗扰环节则利用扩张状态观 测器对负载电流等非严格重复扰动进行估计, 并将其影响提前在控制端抵消, 使得学习过程免受非严格重复的负面 影响. MATLAB/Simulink仿真验证表明, 该方法对抑制短时扰动造成的输出电压周期波动有良好效果, 逆变器稳定 性得到进一步提高.

英文摘要

      Error is the main source to generate the control input and directly decides the effect of the current time control. In this paper, the error effective value is utilized to describe the variation of error energy. According to the preset threshold of error variation intensity, the non-repetitive information is selected/eliminated to improve the quality of information supplied for the learning controller. Learning controller is implemented by means of a unit positive feedback component with only one 2N-orders low-pass filter, where convergence condition along the period domain is analyzed, and the filter cut-off frequency can be obtained based on the frequency of inverter fundamental wave and each harmonics. The state influence caused by non-repetitive disturbance information is estimated by an extended state observer and rejected by the equivalent control input in advance, and negative effects from non-repetitiveness is avoided for the learning process. Matlab simulation shows that a better tracking performance can be obtained when suppressing short-time disturbance by using the proposed algorithm, and inverter stability is enhanced.