Dead-Time Compensation with DC Offset Current Elimination Method Using Three-Level Operation for Dual Active Bridge DC-DC Converter

2018 ◽  
Author(s):  
Jun-Ichi Itoh ◽  
Kengo Kawauchi ◽  
Hayato Higa
Keyword(s):  
Dead Time ◽  
Elimination Method ◽  
Dc Offset ◽  
Dual Active Bridge ◽  
Dead Time Compensation

Current Reduction Method for Dual Active Bridge Converter in Non-linear Dead-time Compensation Method

2020 ◽  
Vol 140 (3) ◽  
pp. 175-183
Author(s):  
Kengo Kawauchi ◽  
Hayato Higa ◽  
Hiroki Watanabe ◽  
Keisuke Kusaka ◽  
Jun-ichi Itoh
Keyword(s):  
Reduction Method ◽  
Dead Time ◽  
Compensation Method ◽  
Dual Active Bridge ◽  
Non Linear ◽  
Dead Time Compensation ◽  
Current Reduction

Dead-time Compensation Method for Dual Active Bridge Converter with Three-level Operation

2018 ◽  
Vol 138 (12) ◽  
pp. 944-945
Author(s):  
Kengo Kawauchi ◽  
Hayato Higa ◽  
Keisuke Kusaka ◽  
Jun-ichi Itoh
Keyword(s):  
Dead Time ◽  
Compensation Method ◽  
Dual Active Bridge ◽  
Dead Time Compensation

scholarly journals Adaptive dead time compensation for cross-period single phase shift control of dual active bridge converters

2020 ◽  
Vol 18 ◽  
pp. 327-332
Author(s):  
Szabolcs Veréb ◽  
◽  
András Futó ◽  
Zoltan Sutto ◽  
Attila Balogh ◽  
...  
Keyword(s):  
Phase Shift ◽  
Single Phase ◽  
Dead Time ◽  
Dual Active Bridge ◽  
Shift Control ◽  
Dead Time Compensation

scholarly journals Dead-Time Compensation for the First-Order Dead-Time Processes: Towards a Broader Overview

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1519
Author(s):  
Mikulas Huba ◽  
Pavol Bistak ◽  
Damir Vrancic ◽  
Katarina Zakova
Keyword(s):  
Degrees Of Freedom ◽  
Dead Time ◽  
Feedforward Control ◽  
Structural Instability ◽  
Smith Predictor ◽  
Actual Process ◽  
Delayed Systems ◽  
First Order ◽  
Plant Modelling ◽  
Dead Time Compensation

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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