Journal
CONTROL ENGINEERING PRACTICE
Volume 143, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.conengprac.2023.105790
Keywords
Grid-tied inverters; Linear matrix inequalities; Particle swarm optimization; Robust control; Test-driven design
Ask authors/readers for more resources
This work presents a new automated test-driven design procedure for robust and optimized current controllers applied to LCL-filtered grid-tied inverters. The design of control gains is guided by high-fidelity simulations and particle swarm optimization algorithm, considering various normal and abnormal operating conditions. The proposed design ensures superior performance compared with other current control designs.
Many current controllers are designed based on linear models, which may lead to poor performance when limiting its variables to a safe operation region, or even lead to instability when subject to abnormal operation conditions. Taking that as motivation, the contribution of this work is a new automated test-driven design procedure for robust and optimized current controllers applied to LCL-filtered grid-tied inverters. The design of the control gains towards an optimal solution is oriented by high-fidelity simulations of the converter, covering tests under normal and abnormal operating conditions, such as: reference tracking, grid impedance variations, voltage sags, harmonic compliance, and current and voltage limitations. A particle swarm optimization algorithm is used to evolve the control gains in a computationally efficient way, and linear matrix inequalities are employed to accelerate the optimization process and to provide a theoretical certificate of robust stability. Results are obtained in both controller hardware-in-the-loop testbed and an experimental 5.4 kW prototype, illustrating cases where the proposed design ensures superior performance under normal and abnormal grid conditions when compared with three other current control designs from the literature.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available