scholarly journals Dead Time Compensation of Grid-connected Inverter Using Resonant Controller

2011 ◽  
Vol 16 (6) ◽  
pp. 569-576 ◽  
Author(s):  
Sang-Hyup Han ◽  
Jong-Hyoung Park ◽  
Heung-Geun Kim ◽  
Honn-Yong Cha ◽  
Tea-Won Chun ◽  
...  
Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5535
Author(s):  
Kangsoon Ahn ◽  
Yongseung Oh ◽  
Wonseok Oh ◽  
Kyumin Cho

This study presents a novel switching scheme for three-level neutral point clamped (NPC) inverters. The proposed switching method independently drives the upper- and lower-arm elements of the inverter based on the polarity information of the reference current. The proposed switching scheme does not require the inclusion of dead-time for each switching, except when the current polarity changes. Therefore, unlike the conventional inverter switching method, dead-time compensation is not needed, and the possibility of an arm-short accident is prevented. In this study, a switching procedure is detailed, and the operation mode analysis of the proposed switching scheme is presented. The effectiveness of the proposed switching method is verified experimentally by application to a grid-connected inverter that requires inverter current control.


2017 ◽  
Vol 22 (2) ◽  
pp. 166-174
Author(s):  
Ui-Seok Seong ◽  
Jae-Suk Lee ◽  
Seon-Hwan Hwang ◽  
Jang-Mok Kim

2020 ◽  
Vol 140 (3) ◽  
pp. 175-183
Author(s):  
Kengo Kawauchi ◽  
Hayato Higa ◽  
Hiroki Watanabe ◽  
Keisuke Kusaka ◽  
Jun-ichi Itoh

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1519
Author(s):  
Mikulas Huba ◽  
Pavol Bistak ◽  
Damir Vrancic ◽  
Katarina Zakova

The article reviews the results of a number of recent papers dealing with the revision of the simplest approaches to the control of first-order time-delayed systems. The concise introductory review is extended by an analysis of two discrete-time approaches to dead-time compensation control of stable, integrating, and unstable first-order dead-time processes including simple diagnostics of the model used and focusing on the possibility of simplified but reliable plant modelling. The first approach, based on the first historically known dead-time compensator (DTC) with possible dead-beat performance, is based on the reconstruction of the actual process variables and the compensation of input disturbances by an extended state observer (ESO). Such solutions play an important role both in a disturbance observer (DOB) based control and in an active disturbance rejection control (ADRC). The second approach considered comes from the Smith predictor with two degrees of freedom, which combines feedforward control with output disturbance reconstruction and compensation by the parallel plant model. It is shown that these two approaches offer advantageous properties in the case of actuator limitations, in contrast to the commonly used PID controllers. However, when applied to integrating and unstable first-order systems, the unconstrained and possibly unobservable output disturbance signal of the second solution must be eliminated from the control loop, due to the hidden structural instability of the Smith predictor-like solutions. The modified solutions, usually referred to as filtered Smith predictor (FSP), then no longer provide a disturbance signal and thus no longer fully fit into the concept of Industry 4.0, which is focused on further optimization, predictive maintenance in dynamic systems, diagnosis, fault detection and fault identification of dynamic processes and forms the basis for the digitalization of smart production. Nevertheless, the detailed analysis of the elimination of the unstable disturbance response mode is also worth mentioning in terms of other possible solutions. The application of both approaches to the control of a thermal process shows almost equivalent quality, but with different dependencies on the tuning parameters used. It is confirmed that a more detailed identification of the controlled process and the resulting higher complexity of the control algorithms does not necessarily lead to an increase in the resulting quality of the transients, which underlines the importance of the simplified plant modelling for practice.


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