An Output-Bounded Model Predictive Control with Equivalently Variable Sampling Interval for Current-Source Converter

2018 ◽  
Author(s):  
Hang Gao ◽  
Bin Wu ◽  
Dewei Xu ◽  
Navid R. Zargari
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Current Source ◽  
Sampling Interval ◽  
Variable Sampling Interval ◽  
Variable Sampling ◽  
Current Source Converter

ON MODEL PREDICTIVE CONTROL OF QUASI-RESONANT CONVERTERS

2009 ◽  
Vol 18 (07) ◽  
pp. 1167-1183 ◽  
Author(s):  
FARZAD TAHAMI ◽  
MEHDI EBAD
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Linear Models ◽  
Control Strategies ◽  
Sampling Interval ◽  
Control Synthesis ◽  
Resonant Converters ◽  
Control Input ◽  
Model Approximation ◽  
Dynamic Matrix

In this paper, different model predictive control synthesis frameworks are examined for DC–DC quasi-resonant converters in order to achieve stability and desired performance. The performances of model predictive control strategies which make use of different forms of linearized models are compared. These linear models are ranging from a simple fixed model, linearized about a reference steady state to a weighted sum of different local models called multi model predictive control. A more complicated choice is represented by the extended dynamic matrix control in which the control input is determined based on the local linear model approximation of the system that is updated during each sampling interval, by making use of a nonlinear model. In this paper, by using and comparing these methods, a new control scheme for quasi-resonant converters is described. The proposed control strategy is applied to a typical half-wave zero-current switching QRC. Simulation results show an excellent transient response and a good tracking for a wide operating range and uncertainties in modeling.

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