Integral Sliding-Mode Control-Based Direct Power Control for Three-Level NPC Converters

被引:16
作者
Lin, Hao [1 ]
Leon, Jose I. [1 ,2 ]
Luo, Wensheng [1 ]
Marquez, Abraham [2 ]
Liu, Jianxing [1 ]
Vazquez, Sergio [2 ]
Franquelo, L. G. [1 ,2 ]
机构
[1] Harbin Inst Technol, Dept Control Sci & Engn, Harbin 150001, Peoples R China
[2] Univ Seville, Elect Engn Dept, Seville 41004, Spain
基金
中国国家自然科学基金;
关键词
three-level neutral-point-clamped converter; integral sliding-mode control; extended state observer; radial basis function neural network; MODULATION TECHNIQUES; RECTIFIER; TRACKING; SYSTEMS; DESIGN;
D O I
10.3390/en13010227
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Three-level neutral-point-clamped (NPC) converter is widely used in energy conversion systems due to its good properties for high-power systems presenting output waveforms with reduced harmonic distortion. To obtain better system performance, an integral sliding-mode control (ISMC)-based direct power control (DPC) strategy is proposed for NPC converters. The controller achieves three objectives. First, an extended state observer (ESO)-based ISMC strategy, to enforce the active and reactive power to their reference values, is applied in the power tracking loop. ESO is used to reduce the influence of parameter uncertainties. Next, in the voltage regulation loop, a radial basis function neural network (RBFNN)-based adaptive ISMC strategy is applied to regulate the DC-link voltage. RBFNN is used to estimate the load variation, which is considered as a disturbance, to improve the system disturbance rejection ability. An adaptive law is used in the controller to reduce the chattering of reference active power which can reduce the current harmonic distortion. Finally, a proportional-integral (PI) control strategy is applied in the voltage balancing loop to achieve voltage balance between two DC-link capacitors. Experimental results show the effectiveness and superiority of the proposed control strategy for the NPC power converter compared with PI-based DPC strategy.
引用
收藏
页数:20
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