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Adaptive reference model predictive control with improved performance for voltage-source inverters
File | Description | Size | Format | |
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07864322.pdf | Accepted version | 2.11 MB | Adobe PDF | View/Open |
Title: | Adaptive reference model predictive control with improved performance for voltage-source inverters |
Authors: | Yang, Y Tan, SC Hui, SYR |
Item Type: | Journal Article |
Abstract: | Power converters under the model predictive control (MPC) inherently suffer from nonignorable steady-state residuals in its control outputs when it exists a mismatch in the parameters between the actual system in control and the system's model adopted in the control. In this brief, an adaptive reference MPC (ARMPC) is proposed in response to this issue. Unlike those conventional derivatives of MPC, the ARMPC is designed to track the so-called virtual references instead of the actual references. The virtual references are generated by a flexibly modeled virtual multiple input multiple output system. Consequently, additional tuning is not required for different operating conditions. ARMPC has been applied to a single-phase full-bridge voltage-source inverter with both resistive and resistive-inductive loads. It is experimentally verified that the proposed ARMPC can significantly attenuate the steady-state offsets in the environment of model mismatch (which is an inherent problem of MPC without significantly sacrifice transient performance). Also, a demonstration that ARMPC renders a consistent attenuation of steady-state errors than the conventional MPC with integrator is provided. More importantly, ARMPC shows better transient performance than the MPC with integrator for some cases. |
Issue Date: | 1-Mar-2018 |
Date of Acceptance: | 11-Feb-2017 |
URI: | http://hdl.handle.net/10044/1/60404 |
DOI: | http://dx.doi.org/10.1109/TCST.2017.2670529 |
ISSN: | 1063-6536 |
Start Page: | 724 |
End Page: | 731 |
Journal / Book Title: | IEEE Transactions on Control Systems Technology |
Volume: | 26 |
Issue: | 2 |
Copyright Statement: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | 0906 Electrical And Electronic Engineering 0102 Applied Mathematics Industrial Engineering & Automation |
Publication Status: | Published |
Online Publication Date: | 2017-02-24 |
Appears in Collections: | Electrical and Electronic Engineering Faculty of Engineering |