Adaptive Optimal Tracking Control for a Flywheel Energy Storage System without the Use of a Model
Received: 5 April 2025 | Revised: 4 May 2025 and 22 May 2025 | Accepted: 31 May 2025 | Online: 16 July 2025
Corresponding author: Thi Thanh Hoa Lai
Abstract
This study presents an adaptive optimal tracking control method for a Flywheel Energy Storage System (FESS) using an Induction Motor (IM) without requiring an accurate system model. The control system employs a Deep Neural Network (DNN) identifier combined with an optimal controller and a Critic Neural Network (CNN) to ensure that the FESS output power follows the reference power value. The simulation results demonstrate that the proposed method achieves high accuracy and strong self-adaptation to system variations.
Keywords:
deep neural network, IM-FESS, optimal control, dynamic control, dynamic neural networkDownloads
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