Integral Sliding Mode Compound Control Strategy for Quasi-Z Source Grid-Connected Inverter

Meichen, Pan; Chen, Caixue; Zhang, Da

doi:10.1109/appeec45492.2019.8994538

Cited by 1 publication

(3 citation statements)

References 7 publications

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“…where f ( x , t ) and g ( x , t ) are functions of state variable; u represents the switching state,

u = \{ { \def\eqcellsep{&}\begin{array}{@{}*{1}{l}@{}} {1,\quad {\text{shoot--through state}}}\\ {0,\quad {\text{non-shoot--through state}}} \end{array} }

. Based on the Kirchhoff's Current Law (KCL) and Kirchhoff's Voltage Law (KVL), the state space equation of the photovoltaic quasi‐Z‐source inverter system is derived by incorporating the equivalent circuit models for both the shoot‐through and non‐shoot‐through states [21].

([], \begin{matrix} d i_{normalL 1} (/) d t \\ d i_{normalL 2} (/) d t \\ d u_{normalC 1} (/) d t \\ d u_{normalC 2} (/) d t \\ d u_{normalP V} (/) d t \end{matrix}) = ([], \begin{matrix} \frac{u_{normalP V} - u_{normalC 1}}{L} \\ - \frac{u_{normalC 2}}{L} \\ \frac{i_{normalL 1} - i_{normald c}}{C} \\ \frac{i_{normalL 2} - i_{normald c}}{C} \\ \frac{U_{normalS} - u_{P V}}{C_{p<...}} \end{matrix})

…”

Section: Average State Model Of Photovoltaic Quasi‐z‐source Invertermentioning

confidence: 99%

“…where f(x, t) and g(x, t) are functions of state variable; u represents the switching state, u = { 1, shoot-through state 0, non-shoot-through state . Based on the Kirchhoff 's Current Law (KCL) and Kirchhoff 's Voltage Law (KVL), the state space equation of the photovoltaic quasi-Z-source inverter system is derived by incorporating the equivalent circuit models for both the shoot-through and non-shoot-through states [21].…”

Section: Average State Model Of Photovoltaic Quasi-z-source Invertermentioning

confidence: 99%

“…As a control strategy for non-linear systems, sliding mode variable structure control enables the system to perform small amplitude and high-frequency motion along the specified state under certain conditions [9]. This approach significantly reduces dependence on the mathematical model of the control system and exhibits improved robustness against parameter uncertainties and variations.…”

Section: Introductionmentioning

confidence: 99%

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Quasi‐Z based adaptive sliding mode control for three‐phase photovoltaic grid‐connected system

Chen,

Meng,

Yan

et al. 2023

IET Power Electronics

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Considering the non‐linear characteristics of both the input and output of photovoltaic (PV) modules and quasi‐Z‐source inverters, as well as the unpredictable natural factors such as large disturbances caused by changes in illumination and temperature, an average state model for the PV quasi‐Z‐source inverter is established. This paper uses the output current of photovoltaic module, DC‐link capacitor voltage and its integral as state variables, then an adaptive reaching law with second‐order sliding mode characteristics is designed by combining with power reaching law and variable speed reaching law. By using the sliding mode controller based on the adaptive reaching law to control the stability of the DC‐link voltage of the quasi‐Z‐source inverter and the small capacitor voltage ripple, the photovoltaic system can operate stably at the maximum power point when the temperature and illumination conditions change abruptly, and the grid‐connected effect is improved. Through SIMULINK and RT‐LAB real‐time simulation, the effectiveness of the proposed adaptive sliding mode control strategy is verified when the environment changes, which effectively improves the dynamic response speed and grid‐connected effect of the system, and ensures the global robustness of the grid‐connected system.

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“…where f ( x , t ) and g ( x , t ) are functions of state variable; u represents the switching state,

u = \{ { \def\eqcellsep{&}\begin{array}{@{}*{1}{l}@{}} {1,\quad {\text{shoot--through state}}}\\ {0,\quad {\text{non-shoot--through state}}} \end{array} }

([], \begin{matrix} d i_{normalL 1} (/) d t \\ d i_{normalL 2} (/) d t \\ d u_{normalC 1} (/) d t \\ d u_{normalC 2} (/) d t \\ d u_{normalP V} (/) d t \end{matrix}) = ([], \begin{matrix} \frac{u_{normalP V} - u_{normalC 1}}{L} \\ - \frac{u_{normalC 2}}{L} \\ \frac{i_{normalL 1} - i_{normald c}}{C} \\ \frac{i_{normalL 2} - i_{normald c}}{C} \\ \frac{U_{normalS} - u_{P V}}{C_{p<...}} \end{matrix})

…”

Section: Average State Model Of Photovoltaic Quasi‐z‐source Invertermentioning

confidence: 99%

Section: Average State Model Of Photovoltaic Quasi-z-source Invertermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quasi‐Z based adaptive sliding mode control for three‐phase photovoltaic grid‐connected system

Chen,

Meng,

Yan

et al. 2023

IET Power Electronics

View full text Add to dashboard Cite

show abstract

Integral Sliding Mode Compound Control Strategy for Quasi-Z Source Grid-Connected Inverter

Cited by 1 publication

References 7 publications

Quasi‐Z based adaptive sliding mode control for three‐phase photovoltaic grid‐connected system

Quasi‐Z based adaptive sliding mode control for three‐phase photovoltaic grid‐connected system

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