LAPSE:2019.1069
Published Article
LAPSE:2019.1069
Optimal Nonlinear Adaptive Control for Voltage Source Converters via Memetic Salp Swarm Algorithm: Design and Hardware Implementation
Yueping Jiang, Xue Jin, Hui Wang, Yihao Fu, Weiliang Ge, Bo Yang, Tao Yu
September 30, 2019
Voltage source converter (VSC) has been extensively applied in renewable energy systems which can rapidly regulate the active and reactive power. This paper aims at developing a novel optimal nonlinear adaptive control (ONAC) scheme to control VSC in both rectifier mode and inverter mode. Firstly, the nonlinearities, parameter uncertainties, time-varying external disturbances, and unmodelled dynamics can be aggregated into a perturbation, which is then estimated by an extended state observer (ESO) called high-gain perturbation observer (HGPO) online. Moreover, the estimated perturbation will be fully compensated through state feedback. Besides, the observer gains and controller gains are optimally tuned by a recent emerging biology-based memetic salp swarm algorithm (MSSA), the utilization of such method can ensure a desirably satisfactory control performance. The advantage of ONAC is that even though the operation conditions are constantly changing, the control performance can still be maintained to be globally consistent. In addition, it is noteworthy that in rectifier mode only the reactive power and DC voltage are required to be measured, while in inverter mode merely the reactive power and active power have to be measured. At last, in order to verify the feasibility of ONAC in practical application, a hardware experiment is implemented.
Keywords
hardware experiment, memetic salp swarm algorithm, optimal nonlinear adaptive control, perturbation observer, voltage source converter
Suggested Citation
Jiang Y, Jin X, Wang H, Fu Y, Ge W, Yang B, Yu T. Optimal Nonlinear Adaptive Control for Voltage Source Converters via Memetic Salp Swarm Algorithm: Design and Hardware Implementation. (2019). LAPSE:2019.1069
Author Affiliations
Jiang Y: NARI Technology Co. Ltd., Nanjing 211106, China
Jin X: NARI Technology Co. Ltd., Nanjing 211106, China
Wang H: NARI Technology Co. Ltd., Nanjing 211106, China
Fu Y: NARI Technology Co. Ltd., Nanjing 211106, China
Ge W: NARI Technology Co. Ltd., Nanjing 211106, China
Yang B: Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China
Yu T: College of Electric Power, South China University of Technology, Guangzhou 510640, China [ORCID]
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Journal Name
Processes
Volume
7
Issue
8
Article Number
E490
Year
2019
Publication Date
2019-08-01
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr7080490, Publication Type: Journal Article
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LAPSE:2019.1069
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doi:10.3390/pr7080490
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Sep 30, 2019
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Sep 30, 2019
 
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Original Submitter
Calvin Tsay
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