A Computationally Efficient Robust Direct Model Predictive Control for Medium Voltage Induction Motor Drives

Tregubov, Andrei; Καραμανάκος, Πέτρος; Ortombina, Ludovico

doi:10.1109/ecce47101.2021.9595296

Cited by 6 publications

(5 citation statements)

References 21 publications

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“…To further expand the applicability to non-linear systems, linearization approaches have been proposed in [133], [134] with the goal to predict and control the non-linear behavior of the neutral point potential of a 3L-NPC inverter. First investigations on the robustness of the SDA to parameter mismatches were presented in [135], [136] and followed-up by an online parameter estimation for the SDA in [137].…”

Section: E Long-horizon Fcs-mpcmentioning

confidence: 99%

Model-Predictive Control of Multilevel Inverters: Challenges, Recent Advances, and Trends

Harbi

Rodríguez

Liegmann

et al. 2023

IEEE Trans. Power Electron.

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Model predictive control (MPC) has emerged as a promising control method in power electronics, particularly for multi-objective control problems such as multilevel inverter (MLI) applications. Over the past two decades, improving the performance of MPC and tackling its technical challenges such as computational load, modeling accuracy, cost function design and weighting factors selection have attracted great interest in power electronics. This article aims to discuss the current state of MPC strategies for MLI applications, describing the significance of each challenge with the reported effective solutions. Through this review, the MPC methods are categorized into two groups, direct MPC (without modulator) and indirect MPC (with modulator). The recent advances of each category are presented and analyzed, focusing on direct MPC as the most applied method for MLI topologies. In addition, some of the important concepts are experimentally validated through a case study and compared under the same operating conditions to evaluate the performance and highlight their features. Finally, the future trends of MPC for MLI applications are discussed based on the current state and reported developments.

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Section: E Long-horizon Fcs-mpcmentioning

confidence: 99%

Model-Predictive Control of Multilevel Inverters: Challenges, Recent Advances, and Trends

Harbi

Rodríguez

Liegmann

et al. 2023

IEEE Trans. Power Electron.

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“…Since the harmonic current, and thus optimal reference trajectory, are derived based on the nominal value of X σ , deviations from it will affect the tracking performance of the controller. Nevertheless, there are simple mechanisms that can easily provide the accurate value of X σ , and hence mitigate this problem [28]. As for the changes in X m , these affect the estimation of the rotor flux, since this is merely estimated in a feedforward manner based on X σ and X m , thus it lacks any integrating action, see [15,.…”

Section: A Robustness To Machine Parameter Variationsmentioning

confidence: 99%

Gradient-Based Predictive Pulse Pattern Control of Medium-Voltage Drives—Part II: Performance Assessment

Begh

Καραμανάκος

Geyer

et al. 2022

IEEE Trans. Power Electron.

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In this paper, the performance of gradient-based predictive pulse pattern control (GP 3 C) is evaluated for a medium-voltage variable speed drive consisting of a threelevel neutral point clamped (NPC) inverter and a mediumvoltage induction machine. To this end, real-time tests are performed in a hardware-in-the-loop (HIL) environment, which along with extensive simulation studies, elucidate the potential of and performance gains achieved with GP 3 C. As shown, by manipulating offline-computed optimized pulse patterns (OPPs) in real time such that the stator current of the machine follows a pre-calculated optimal current trajectory, superior steady-state and transient performance can be achieved. Specifically, the current total demand distortion (TDD) is significantly reduced compared with established control methods, such as field oriented control (FOC) with space vector modulation (SVM), while shorter settling times during transients are achieved. Finally, to complete the assessment of the control method of interest, real-time implementation aspects are discussed in detail.

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“…More specifically, the proposed algorithm (a) has modest computational complexity, and (b) shows a high degree of robustness. 1 To achieve the former, the MPC problem is formulated by taking advantage of the fact that MV drives need to operate at low switching frequencies of a few hundred hertz, meaning that the control action changes only a few times within the fundamental period. In doing so, two different horizons are defined in the MPC problem, namely the control and prediction horizons, that can be manipulated to keep the computational complexity at bay while still achieving a superior drive performance.…”

Section: Introductionmentioning

confidence: 99%

“…In doing so, two different horizons are defined in the MPC problem, namely the control and prediction horizons, that can be manipulated to keep the computational complexity at bay while still achieving a superior drive performance. 1 This paper is an extension of [1]. Herein, as compared with [1], a deeper theoretical analysis of the proposed method is presented along with its verification with real-time tests performed in a hardware-in-the-loop (HIL) environment.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Long-Horizon Robust Direct Model Predictive Control for Medium-Voltage Induction Motor Drives With Reduced Computational Complexity

Tregubov

Καραμανάκος

Ortombina

2023

IEEE Trans. on Ind. Applicat.

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This paper proposes a long-horizon direct model predictive control (MPC) with reference tracking for mediumvoltage (MV) drives that achieves favorable steady-state and transient behavior. However, as MPC is a model-based method, it is susceptible to parameter mismatches and variations of the machine. Moreover, even though a long prediction horizon significantly improves the steady-state behavior of the drive, it significantly increases the computational complexity of the direct MPC problem, rendering its real-time implementation a challenging-if not impossible-task. Motivated by these shortcomings of long-horizon direct MPC, this paper also aims to address them by enhancing the robustness of the developed control strategy, while keeping its computational complexity modest. To achieve the former, a prediction model suitable for MV drive systems is adopted that facilitates the effective estimation of the total leakage inductance of the machine. For the latter, the objective function of the MPC problem is formulated such that, even though the drive behavior is computed over a long prediction interval, only a few changes in the candidate switch positions are considered. The effectiveness of the proposed modeling, control, and estimation approaches is validated with hardware-in-the-loop (HIL) tests for an MV drive consisting of a three-level neutral point clamped (NPC) inverter and an induction machine (IM).Index Terms-AC drives, medium-voltage (MV) drives, model predictive control (MPC), direct control, robust control, hardware-in-the-loop (HIL) simulations.

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A Computationally Efficient Robust Direct Model Predictive Control for Medium Voltage Induction Motor Drives

Cited by 6 publications

References 21 publications

Model-Predictive Control of Multilevel Inverters: Challenges, Recent Advances, and Trends

Model-Predictive Control of Multilevel Inverters: Challenges, Recent Advances, and Trends

Gradient-Based Predictive Pulse Pattern Control of Medium-Voltage Drives—Part II: Performance Assessment

Long-Horizon Robust Direct Model Predictive Control for Medium-Voltage Induction Motor Drives With Reduced Computational Complexity

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