Abstract

This paper proposes a Q-learning-based state feedback suboptimal controller to solve the current control problem of three-phase grid-connected LCL coupled inverters with unknown circuit parameters. In practice, the circuit parameters of the inverters will change obviously for reasons such as calculation errors, external environment and operation aging, which makes the dynamics of the inverter system become unknown. With the circuit’s model of the LCL inverters and the reference current dynamic, an augmented system is constructed and a discounted performance function is formulated as the optimal objective of current control which transform it into a H∞ tracking control. Using Q-learning algorithm with model-free characteristics, a current controller is proposed in which an iterative reinforcement learning (RL) algorithm is embedded. Simulations are presented to verify the valid of the proposed control scheme, where especially the results shows that it can keep excellent control performance under the condition of inverter parameter mutation and grid voltage distortion.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.