Design and Optimization of Control System for More Electric Aircraft Power Systems Using Adaptive Tabu Search Algorithm Based on State-Variables-Averaging Model

• Published in: IEEE access 2024, Vol.12, p.76579-76588
• Main Authors: Phosung, Ratapon, Areerak, Kongpan, Areerak, Kongpol
• Format: Article
• Language: English
• Subjects: Adaptive algorithms; Adaptive control; Adaptive systems; adaptive tabu search algorithm; Aircraft; Artificial intelligence; Capacitor banks; Capacitors; Computing time; Control systems design; Controllers; Design optimization; Eigenvalues; Electric power systems; Electric vehicles; Energy efficiency; Fly by wire control; Hardware-in-the-loop simulation; Mathematical models; More electric aircraft; Passenger safety; Power system stability; Safety; Search algorithms; Search methods; Stability analysis; State variable; state-variables-averaging model; Tabu search; Thermal stability; vector control; Voltage control
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3406855

An important reflection of the overall efficiency, reliability, and passenger safety of a more electric aircraft (MEA) is the output performance of its electrical power system (EPS) controller. This output performance encompasses the rise time, setting time, and percent undershoot of the voltage across the capacitor bank. Therefore, this article presents an optimal controller design using an artificial intelligence method called the adaptive tabu search (ATS) algorithm. The state-variables-averaging model is applied with the ATS algorithm to reduce computational time. Moreover, stability analysis based on the eigenvalue theorem is used as the penalty condition during the searching process to avoid unstable operation. The output performance of the proposed controller design is superior to that of the conventional controller design. All design results are verified by good agreement with MATLAB and hardware-in-the-loop (HIL) simulations.