Title of article
Comparisons between Generalized Predictive Control and Linear Controllers in Multi-Input DC-DC Boost Converter
Author/Authors
Ehsani, Mohsen Department of Electrical and Computer Engineering - Iran University of Science and Technology, Tehran, Iran , Saeidi, Masood Department of Electrical and Computer Engineering - Iran University of Science and Technology, Tehran, Iran , Radmanesh, Hamid Electrical Engineering Department - Shahid Sattari Aeronautical University of Science and Technology, Tehran, Iran , Abrishamifar, Adib Department of Electrical and Computer Engineering - Iran University of Science and Technology, Tehran, Iran
Pages
8
From page
27
To page
34
Abstract
In this paper, the linear state-space model of the multi-input DC-DC boost converter is obtained and based on, a linear SISO model is calculated. Model predictive control (MPC) offers a novel method of designing in the power electronic converters. The application to DC-DC converters offers real benefits because of having simple tuning technique and analytical guaranteed stability. The weakness of this converter is non minimum phase behavior. One of the methods of implementation MPC controller is Generalized Predictive Control (GPC) which is compatible with non-minimum phase systems but due to simple implementation, using of the linear controller is more popular in power electronics control system. GPC has some advantage such as fast dynamic and robustness in the nonlinear system however main advantage of linear controllers is its low steady state error. The main idea of this paper is the investigation performance of GPC and linear controller in the multi-input DC-DC boost converter and camper with PI controller in term of dynamic, steady-state error, and robustness and run time in a microcontroller. The resulting of this comparison is critically assessed in simulation and algorithms ruining time has been compared in microcontroller hardware.
Keywords
MPC , boost converter , linear controller , runtime
Journal title
Astroparticle Physics
Serial Year
2020
Record number
2465387
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