scholarly journals An Observer-Based Finite Control Set Model Predictive Control for Three-Phase Power Converters

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Tao Liu ◽  
Changliang Xia ◽  
Xin Gu ◽  
Tingna Shi
Keyword(s):  
Time Delay ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Power Converters ◽  
Experimental Testing ◽  
Power Converter ◽  
Three Phase ◽  
Finite Control ◽  
Control Set ◽  
Discrete Mathematical Model

Finite control set model predictive control (FCS-MPC) for three-phase power converters uses a discrete mathematical model of the power converter to predict the future current value for all possible switching states. The circuit parameters and measured input currents are necessary components. For this reason, parameter error and time delay of current signals may degrade the performance of the control system. In the previous studies of the FCS-MPC, few articles study these aspects in detail and almost no method is proposed to avoid these negative influences. This paper, first, investigates the negative impacts of inductance inaccuracy and AC-side current distortion due to the time delay caused by filter on FCS-MPC system. Then, it proposes an observer-based FCS-MPC approach with which the inductance error can be corrected, the current signal’s time delay caused by filter can be compensated, and therefore the performance of FCS-MPC will be improved. At last, as an example, it illustrates the effectiveness of the proposed approach with experimental testing results for a power converter.

scholarly journals Performance Assessment of Grid Forming Converters Using Different Finite Control Set Model Predictive Control (FCS-MPC) Algorithms

2019 ◽  
Vol 9 (17) ◽  
pp. 3513 ◽  
Author(s):  
Mohammed Alhasheem ◽  
Frede Blaabjerg ◽  
Pooya Davari
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Point Of View ◽  
Voltage Source ◽  
Voltage Source Converter ◽  
Linear Load ◽  
Three Phase ◽  
Comparable Performance ◽  
Finite Control ◽  
Control Set

Finite control set model predictive control (FCS-MPC) methods in different power electronic applications are gaining considerable attention due to their simplicity and fast dynamics. This paper introduces an assessment of the two-level three-phase voltage source converter (2L-VSC) utilizing different MPC schemes with and without a modulation stage. In order to perform such a comparative evaluation, 2L-VSC efficiency and total harmonics distortion of the voltage (THDv) have been investigated, when considering a linear load. The results demonstrate the performance of different MPC algorithms through an experimental verification on a Danfoss converter, and a set of analyses have been studied using the PLECS and MATLAB/SIMULINK together. It can be concluded that a comparable performance is achieved by using conventional MPC (CMPC), improved MPC (IMPC), periodic MPC (PMPC), and MPC scheme with modulator (M 2 PC) controllers. The assessment is critical to classify the strategies as mentioned earlier according to their efficiency. Furthermore, it gives a thorough point of view on which algorithm is suitable for the grid-forming applications.

scholarly journals Finite Control Set Model Predictive Control for an LCL-Filtered Grid-Tied Inverter with Full Status Estimations under Unbalanced Grid Voltage

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2691 ◽  
Author(s):  
Xiaotao Chen ◽  
Weimin Wu ◽  
Ning Gao ◽  
Jiahao Liu ◽  
Henry Shu-Hung Chung ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Reactive Power ◽  
Grid Voltage ◽  
Luenberger Observer ◽  
Reference Generator ◽  
Three Phase ◽  
Finite Control ◽  
Control Set ◽  
Unbalanced Grid

This paper proposes a novel finite control set model predictive control (FCS-MPC) strategy with merely grid-injected current sensors for an inductance-capacitance-inductance (LCL)-filtered grid-tied inverter, which can obtain a sinusoidal grid-injected current whether three-phase grid voltages are balanced or not. Compared with the conventional FCS-MPC method, four compositions are added in the proposed FCS-MPC algorithm, where the grid voltage observer (GVO) and Luenberger observer are combined together to achieve full status estimations (including grid voltage, capacitor voltage, inverter-side current, and grid-injected current), while the sequence extractor and the reference generator are applied to eliminate the double frequency ripples of the active or reactive power, or the negative sequence component (NSC) of the grid-injected current caused by the unbalanced grid voltage. Simulation model and experimental platform are established to verify the effectiveness of the proposed FCS-MPC strategy, with full status estimations under both balanced and unbalanced grid voltage conditions.

scholarly journals A Comparison of Finite Control Set and Continuous Control Set Model Predictive Control Schemes for Model Parameter Mismatch in Three-Phase APF

2021 ◽  
Vol 9 ◽  
Author(s):  
Jianfeng Yang ◽  
Yang Liu ◽  
Rui Yan
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Parameter Uncertainty ◽  
Prediction Error ◽  
Continuous Control ◽  
Power Electronic ◽  
Parameter Mismatch ◽  
Three Phase ◽  
Finite Control ◽  
Control Set

Model predictive control (MPC) methods are widely used in the power electronic control field, including finite control set model predictive control (FCS-MPC) and continuous control set model predictive control (CCS-MPC). The degree of parameter uncertainty influence on the two methods is the key to evaluate the feasibility of the two methods in power electronic application. This paper proposes a research method to analyze FCS-MPC and CCS-MPC’s influence on the current prediction error of three-phase active power filter (APF) under parameter uncertainty. It compares the performance of the two model predictive control methods under parameters uncertainty. In each sampling period of the prediction algorithm, different prediction error conditions will be produced when FCS-MPC cycles the candidate vectors. Different pulse width modulation (PWM) results will be produced when CCS-MPC solves the quadratic programming (QP) problem. This paper presents the simulation results and discusses the influence of inaccurate modeling of load resistance and inductance parameters on the control performance of the two MPC algorithms, the influence of reference value and state value on prediction error is also compared. The prediction error caused by resistance mismatch is lower than that caused by inductance mismatch, more errors are caused by underestimating inductance values than by overestimating inductance values. The CCS-MPC has a better control effect and dynamic performance in parameter mismatch, and the influence of parameter mismatch is relatively tiny.

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