Research output per year
Research output per year
Chaoqun Xiang, Xinan Zhang, Tianhao Qie, Tat Kei Chau, Jian Ye, Yang Yu, Herbert Ho Ching Iu, Tyrone Fernando
Research output: Contribution to journal › Article › peer-review
This paper proposes a novel deep deterministic policy gradient (DDPG) assisted integral reinforcement learning (IRL) based control algorithm for the three-phase DC/AC inverter feeding a resistive-inductive (RL) load. The proposed controller autonomously updates its control gains online without the need to know the system model. Excellent steady-state and dynamic system responses are achieved by the proposed control algorithm with reasonably low computational complexity. Moreover, the important initial stabilizing control problem is solved through offline training that uses the DDPG technique. Details of the DDPG based training procedures are presented. Experimental results are presented to verify the efficacy of the proposed IRL based control method.
Original language | English |
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Pages (from-to) | 5529-5539 |
Number of pages | 11 |
Journal | IEEE Journal of Emerging and Selected Topics in Power Electronics |
Volume | 11 |
Issue number | 6 |
Early online date | 12 May 2022 |
DOIs | |
Publication status | Published - 1 Dec 2023 |
Research output: Thesis › Doctoral Thesis