6 Reference Tracking, Topic Chains, and ay-Inversion

2021 ◽  
pp. 193-256
Keyword(s):  
2016 ◽  
Vol 136 (5) ◽  
pp. 676-682 ◽  
Author(s):  
Akihiro Ishimura ◽  
Masayoshi Nakamoto ◽  
Takuya Kinoshita ◽  
Toru Yamamoto

2021 ◽  
Vol 13 (2) ◽  
pp. 505
Author(s):  
Sumaya Jahan ◽  
Shuvra Prokash Biswas ◽  
Md. Kamal Hosain ◽  
Md. Rabiul Islam ◽  
Safa Haq ◽  
...  

The use of different control techniques has become very popular for controlling the performance of grid-connected photovoltaic (PV) systems. Although the proportional-integral (PI) control technique is very popular, there are some difficulties such as less stability, slow dynamic response, low reference tracking capability, and lower output power quality in solar PV applications. In this paper, a robust, fast, and dynamic proportional-integral resonance controller with a harmonic and lead compensator (PIR + HC + LC) is proposed to control the current of a 15-level neutral-point-clamped (NPC) multilevel inverter. The proposed controlled is basically a proportional-integral resonance (PIR) controller with the feedback of a harmonic compensator and a lead compensator. The performance of the proposed controller is analyzed in a MATLAB/Simulink environment. The simulation result represents admirable performance in terms of stability, sudden load change response, fault handling capability, reference tracking capability, and total harmonic distortion (THD) than those of the existing controllers. The responses of the inverter and grid outlets under different conditions are also analyzed. The harmonic compensator decreases the lower order harmonics of grid voltage and current, and the lead compensator provides the phase lead. It is expected that the proposed controller is a dynamic aspirant in the grid-connected PV system.


Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3230
Author(s):  
Milovan Majstorovic ◽  
Marco Rivera ◽  
Leposava Ristic ◽  
Patrick Wheeler

The operation of single-phase Modular Multilevel Converter (MMC) is analyzed in the paper. A mathematical model of the converter is developed and described, based on which the structure and selection of parameters for Classical Control and Optimal Switching State Model Predictive Control (OSS-MPC) are defined. Additionally, the procedure for the determination of circuit parameters, such as submodule capacitance and arm inductance, is described and carried out. The listed control methods are designed and evaluated in Virtual Hardware-in-the-Loop together with single-phase MMC power circuit, regarding three control objectives: AC current control, voltage balancing control and circulating current control. Control methods are evaluated for both steady-state and transient performance and compared based on nine criteria: AC current reference tracking, THD of AC current and voltage, submodule capacitor voltage balancing, total submodule voltage control, circulating current magnitude and THD, number of control parameters and computational complexity. This is the first time that a fair comparison between Classical Control and MPC is considered in literature, resulting in superior performance of both control methods regarding four different criteria and the same performance regarding AC current reference tracking.


2016 ◽  
Vol 49 (7) ◽  
pp. 1079-1084 ◽  
Author(s):  
Anca Maxim ◽  
Clara M. Ionescu ◽  
Constantin F. Caruntu ◽  
Corneliu Lazar ◽  
Robin De Keyser

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