Adaptive Backstepping Control with Online Parameter Estimator for a Plug-and-Play Parallel Converter System in a Power Switcher

Adaptive Backstepping Control with Online Parameter Estimator for a Plug-and-Play Parallel Converter System in a Power Switcher

Guo, Chujia;Zhang, Aimin;Zhang, Hang;Zhang, Lei;
energies 2018 Vol. 11 pp. 3528-
249
guo2018adaptiveenergies

Abstract

This study aims to address the inherent uncertainty in plug loads and load extraction, distributed generation, and the inevitable circulating current in a parallel structure. Therefore, in this paper, an adaptive backstepping control scheme with an online parameter estimator (OPE) for a plug-and-play parallel converter system in a four-port power switcher is proposed. The adaptive backstepping control method was designed in the dq0 coordinate system to suppress the circulating current in the zero-component; the circulating current can be suppressed by using an embedded algorithm and omitting the extra controller. An adaptive update law was designed to weaken the influence of the arbitrary plug and extraction operations in the DC and AC buses to realize the plug-and-play function. The transient tracking performance is governed by the limitation of maximum total errors in the voltage and current. As a result, the settling times of the voltage, current, and power decreased. Additionally, to further improve the system robustness, an online inductance and resistance estimator was established using an optimal algorithm that solves the weighted least squares problem. In the estimator, there are no additional voltage and current sensors needed, and the mean squared error (MSE) of the estimation can be minimized. Simulation studies on a two-converter parallel system with a plug-and-play function were conducted using MATLAB/SIMULINK (R2018b, MathWorks, Natick, MA, USA) to verify the effectiveness of the proposed adaptive backstepping control strategy. The results show that this strategy improves system performance over that of a system with unbalanced parameters among a parallel structure with AC and DC system disturbances caused by arbitrary plug and extraction operations.

Citation

ID: 69772
Ref Key: guo2018adaptiveenergies
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
69772
Unique Identifier:
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet