Computationally-Efficient Model Predictive Control of Dual-Output Multilevel Converter in Hybrid Microgrid

Jayan, Vijesh; Ghias, Amer M. Y. M.

doi:10.1109/tpel.2023.3239437

Cited by 8 publications

(1 citation statement)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results obtained in [20] show that using a long prediction horizon and a short sampling time can reduce torque/current ripples under the FCS-MPC approach. The limits of the long prediction horizon have been studied in [21], taking into account harmonic content, as emphasized in [22,23], where computational complexity is a major issue associated with this method. Furthermore, exact knowledge of the system model is necessary to ensure accurate prediction, which poses challenges in terms of robustness against parameter variation [24].…”

mentioning

confidence: 99%

Non‐linear multivariable permanent magnet synchronous machine control: A robust non‐linear generalized predictive controller approach

Djouadi,

Ouari,

Belkhier

et al. 2023

IET Control Theory & Appl

View full text Add to dashboard Cite

Permanent magnet synchronous motors (PMSM) have become prevalent in industry and play an essential role in managing industrial processes, automation systems, and renewable energy sources due to their superior efficiency, torque, and power density. However, because it operates like a non‐linear system with quick dynamics, variable parameters during operation, and unknown disturbances, PMSM presents challenges for machine control. Non‐linear controls are required to account for the non‐linearities of the permanent magnet synchronous machine. Recently, predictive control techniques for non‐linear multi‐variable systems have gained popularity. In this work, a novel approach to robust non‐linear generalized predictive control (RNGPC) has been developed for PMSM, with the aim of tracking the reference speed while maintaining minimum reactive power, robustness to external disturbances, and parameter uncertainties. A new finite horizon cost function is integrated, with an integral action introduced in the control law. The main advantage of this technique is that it does not require the measurement and observation of external disturbance as well as parametric uncertainties. The control strategy method has been tested in the MATLAB/Simulink environment with various operating conditions. The results showed good robustness against parameter changes and ensured fast convergence.

show abstract

mentioning

confidence: 99%

Non‐linear multivariable permanent magnet synchronous machine control: A robust non‐linear generalized predictive controller approach

Djouadi,

Ouari,

Belkhier

et al. 2023

IET Control Theory & Appl

View full text Add to dashboard Cite

show abstract

Finite-time ESO-based two-stage robust model-free predictive control for flexible interconnecting device

Zhang,

Liu,

Shi

et al. 2024

Electr Eng

View full text Add to dashboard Cite

Role of Harris Hawks optimization–based sliding mode control of AC-DC converter in electric vehicle onboard battery charger

Mathew K.,

Abraham

2024

Advanced Technologies in Electric Vehicles

View full text Add to dashboard Cite

Computationally-Efficient Model Predictive Control of Dual-Output Multilevel Converter in Hybrid Microgrid

Abstract: model predictive control of dual-output multilevel converter in hybrid microgrid. IEEE Transactions On Power Electronics.

Cited by 8 publications

References 43 publications

Non‐linear multivariable permanent magnet synchronous machine control: A robust non‐linear generalized predictive controller approach

Non‐linear multivariable permanent magnet synchronous machine control: A robust non‐linear generalized predictive controller approach

Finite-time ESO-based two-stage robust model-free predictive control for flexible interconnecting device

Role of Harris Hawks optimization–based sliding mode control of AC-DC converter in electric vehicle onboard battery charger

Contact Info

Product

Resources

About