Dual-EKF-Based Fault-Tolerant Predictive Control of Nonlinear DC Microgrids With Actuator and Sensor Faults

• Type: Article in International Scientific Journal
• Date: 2022

Authors

Vafamand, N (Author) Other; Arefi, MM (Author) Other; Asemani, MH (Author) Other; Javadi, MS (Author) Other; Wang, F (Author) Other; Catalao, JPS (Author) FEUP

Journal

Title: IEEE Transactions on Industry Applications

Vol. 58

Pages: 5438-5446

ISSN: 0093-9994

Publisher: IEEE

Indexing

ISI Web of Knowledge - 7 Citations

Scopus - 11 Citations

Other information

Authenticus ID: P-00W-Y50

DOI: 10.1109/tia.2022.3172894

Abstract (EN): The issue of a state estimation-based fault-tolerant controller for direct current (dc) microgrids (MGs) is studied in this article. It is considered that the dc MG contains nonlinear constant power load (CPL) and is subjected to actuator faults. Current sensors are not installed and the voltages of the dc MG are measured in the presence of noise and sensor faults. To estimate the system states, a novel dual-Extended Kalman filter is proposed, which simultaneously estimates the states and faults. The fault- and noise-free estimations are then deployed in a nonlinear Takagi-Sugeno fuzzy predictive controller to regulate the dc MG. The proposed method outperforms the exiting results, being robust against faults and noise. Also, the predictive scheme makes it robust against system uncertainties and forces the system states to converge the desired values, precisely. The accuracy and robustness of the developed method are evaluated and compared to advanced state-of-the-art techniques for a typical dc MG with a resistive load, CPL, and energy storage unit.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9