A Novel Proportion-Integral-Differential Controller Based on Deep Reinforcement Learning for DC/DC Power Buck Converters

2021 ◽  
Author(s):  
Kexin Hu ◽  
Xin Zhang ◽  
Hao Ma
Keyword(s):  
Reinforcement Learning ◽  
Buck Converters ◽  
Dc Power

Unknown Offset Free MPC for Buck Converter

2017 ◽  
Vol 865 ◽  
pp. 175-180
Author(s):  
Po Li ◽  
Rui Nan Liu ◽  
Xiang Hui Ma
Keyword(s):  
Continuous Model ◽  
Buck Converter ◽  
Power Supplies ◽  
Recursive Least Squares ◽  
Buck Converters ◽  
Dc Power ◽  
Control Scheme ◽  
Parameters Uncertainty ◽  
One Step ◽  
And Control

Buck converters are commonly used as DC power supplies. To deal with the parameters uncertainty in R-L (resistance-inductance), an Unknown Offset Free Model Predictive Control (UOFMPC) method for buck converters have been proposed in this paper. Firstly, a continuous model for buck converters is established. Based on it, a discrete model with fixed sampling time is derived and the output of controller is set as the direct switch on/off signals. Secondly, one-step MPC method aimed at optimizing the output voltage with recursive least squares algorithm for parameters identification is given to satisfy the ability of adaptation in parameters. Finally, both the model and control scheme are validated by simulation in MATLAB/Simulink.

scholarly journals STABILITY ANALYSIS OF DC-DC BUCK CONVERTERS

2020 ◽  
Vol 4 (1) ◽  
pp. 01-06
Author(s):  
Ahmed M. Alturas ◽  
Abdulmajed O. Elbkosh ◽  
Othman Imrayed
Keyword(s):  
Stability Analysis ◽  
Pulse Width ◽  
Pulse Width Modulation ◽  
Circuit Simulation ◽  
Buck Converter ◽  
Nonlinear Phenomena ◽  
Buck Converters ◽  
Dc Power ◽  
The Stability ◽  
Oriented Approach

This paper is focusing on the stability analysis of the voltage mode control buck converter controlled by pulse-width modulation (PWM). Using two different approaches, the nonlinear phenomena are investigated in two terms, slow scale and fast scale bifurcation. A complete design-oriented approach for studying the stability of dc-dc power converters and its bifurcation has been introduced. The voltage waveforms and attractors obtained from the circuit simulation have been studied. With the onset of instability, the phenomenon of subharmonics oscillations, quasi-periodicity, bifurcations, and chaos have been observed

Bayes factors for reinforcement-learning models of the Iowa gambling task.

Decision ◽  
2016 ◽  
Vol 3 (2) ◽  
pp. 115-131 ◽  
Author(s):  
Helen Steingroever ◽  
Ruud Wetzels ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Reinforcement Learning ◽  
Iowa Gambling Task ◽  
Bayes Factors ◽  
Gambling Task ◽  
Learning Models ◽  
Reinforcement Learning Models
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