This article proposes an efficient model-free predictive control (EMFPC) based on 2-D sector optimization using an adaptive ultralocal model to address model uncertainty and reduce computational burden. The proposed EMFPC has three key features: first, an adaptive model-free predictive control (MFPC) based on an ultralocal model is leveraged to solve the model uncertainty problems. Different from prior ultralocal models, the focused disturbances and the gain of the system are both estimated online. Second, a novel sector division method based on 2-D optimization strategy is proposed to select the optimal voltage vector (VV) without VV enumeration. Third, the EMFPC has no cost function, and the neutral point voltage is balanced by the redundancy characteristic of small VVs. The cost-function-free model predictive control (MPC) presents a novel idea for simplifying the MPC algorithm. Finally, simulation and experimental results demonstrate that the EMFPC has satisfactory current control performance and stability under model uncertainty conditions. Compared to conventional MPC and MFPC, EMFPC achieves efficiency improvements of 34.8% and 82.6%, respectively.

This article presents a data-driven quantitative multiobjective finite-control-set model predictive control (FCS-MPC) for three-phase three-level neutral point clamped (NPC) inverters, aiming to achieve precise control of both the switching frequency and the neutral point voltage. Considering the switching weighting factor and the neutral point voltage weighting factor as inputs, and the average switching frequency within a fixed sliding window time and the maximum value of the neutral point voltage within another fixed sliding window time as outputs, a compact form dynamic linearization (CFDL) method is employed to construct an equivalent dynamic linearized data model at each dynamic operating point of the closed-loop system. Building upon this data-driven model, a meticulously crafted controller is devised to precisely regulate both the switching frequency and the peak deviation of the neutral-point potential. The simulation and experimental results validate the correctness and demonstrate the superiority of the proposed control approach.

This paper proposes a hybrid unipolar switching level sequence optimal pulse pattern (HUS-OPP) modulation strategy for the SiC/Si hybrid three-phase five-level active-neutral-point-clamped converter (3P-5L-ANPC). The proposed HUS-OPP features quarter-wave and half-wave symmetry, selecting the optimal unipolar switching level sequence across the full modulation range to achieve the best output current waveform quality. To address the challenging coupled capacitor voltage balancing problem in the 3P-5L-ANPC, a simplified balancing method is introduced, which achieves balance of the dc-bus capacitor voltages and the three-phase flying capacitor voltages by inserting extra redundant switching state transitions. This method possesses the characteristics of low real-time computational burden, light data storage requirements, low switching frequency, and ease of implementation. Finally, the calculation method for the HUS-OPP's switching frequency and the storage burden of the optimal angles are derived. Experimental results validate the feasibility and superiority of the proposed strategy.

AbstractThis paper proposes a model predictive control strategy for induction motors driven by three‐level inverters, enabling effective switching frequency adjustment. First, a three‐dimensional satisfaction space optimisation strategy is proposed, eliminating the need for weight coefficient adjustments through self‐constraints and mutual constraints of the optimisation variables. The optimal switching state is selected by comparing the maximum average dwell time within the satisfaction space, thus reducing the inverter switching frequency. Second, switching frequency is treated as an auxiliary optimisation variable, and a dynamic sliding window method is designed to efficiently track switching frequency in variable‐speed systems. The boundaries of the three‐dimensional satisfaction space are adjusted to regulate the switching frequency. Finally, experimental results demonstrate that the proposed strategy maintains the switching frequency of 300 Hz across the entire speed range, achieving excellent dynamic and steady‐state performance at this low switching frequency.

Phase-locked loops (PLLs) are often applied in speed estimation. However, PLLs suffer from certain problems, such as poor dynamic performance and complex parameter tuning, due to their structural design, and both issues are difficult to simultaneously address. This work proposes a fixed-gain filter-based phase-locked loop (FGF-PLL) to address this concern. The FGF-PLL fixes the gain matrix of the Kalman filter to a constant to minimize the computational burden. Meanwhile, only one adjustable parameter exists in the fixed-gain matrix, and its value can be confined to a narrow range through stability analysis. Consequently, the parameter tuning process is more straightforward than that of the conventional PLL. The superiority of the proposed FGF-PLL is experimentally validated using a permanent magnet synchronous machine.

An improved model-free predictive current control with forgetting factor (IMFPCCFF) is presented in this article. The main advantages of previous model-free predictive current control (MFPCC) are that it is only based on detecting the load currents and the current differences. It does not require any parameter of the system. However, this approach has noticeable disadvantages: high requirements on sampling accuracy increase system cost and reduce system reliability, and the reduction of sampling interval in high-frequency converters amplifies sampling noise in adjacent current increment calculations. This article utilizes more historical data to suppress the impact of sampling noise on system performance while introducing a forgetting factor to cope with changes in operating conditions. The feasibility and superiority of the proposedmethod are verified by experiments.

To improve the utilization of the dc-bus voltage and solve the problem of neutral-point voltage (NP-V) unbalance and high common-mode voltage (CMV) in the overmodulation region of three-level neutral-point clamped inverters, a virtual space vector overmodulation (VSV-OVM) strategy considering NP-V balance and CMV suppression is proposed. Based on the hybrid vector correction method, the utilization of dc-bus voltage in the overmodulation region is improved, the computational burden of overmodulation algorithm is alleviated by means of fitting and establishing lookup table. Meanwhile, an effective active NP-V control method with switch states Misalignment protection is designed for the proposed VSV-OVM strategy. Furthermore, the implementation details of the proposed VSV-OVM strategy is elaborated. The experimental results verify that the proposed VSV-OVM has excellent NP-V balance and CMV suppression ability in the overmodulation region, and has higher dc-bus voltage utilization.

This article proposes a new optimal switching sequence model predictive control method for modular multilevel converter (MMC). In this method, the common mode voltage is considered, which makes the model more accurate. The proposed method realizes the optimization of multiple control objectives of output current tracking, circulating current suppression, and SM voltage balancing. The sequence that allows the output current to track its reference value is calculated in the $\alpha -\beta$ coordinate system and the virtual vectors aim to suppress the circulating current without influencing the output current are inserted. Capacitor voltage balancing is achieved by redundant vectors selection and traditional selection algorithm. These control objectives are calculated independently, thus weighting factor is not required. At the same time, the computation burden is reduced by restricting the voltage mutation. This method has a satisfactory dynamic response and steady-state performance, the simulation and experimental results are given to verify the effectiveness of the method.

This article presents a novel finite position set-phase locked loop (FPS-PLL) to extract the rotor position of the permanent-magnet synchronous motors (PMSMs) using a sliding-mode observer. In order to achieve faster convergence speed and less iteration times, Newton iteration method is applied in rotor position retrieval that just needs three iterations. The dichotomy of position combined with a novel cost function is adopted before the Newton iteration ensuring the astringency of iteration. Based on the above design, the calculation of the proposed FPS-PLL is significantly reduced. Additionally, the proposed method does not require complex parameter tuning compared with the conventional PLL. Simulation results proves the effectiveness of the proposed method.

The three-level neutral-point clamped voltage source inverter (3L-NPC-VSI) is widely used in the maglev traction systems due to its high output voltage, large output capacity and low output current harmonics. In order to improve the utilization of the DC-bus voltage, an overmodulation strategy is necessary. This paper proposes an improved overmodulation strategy based on the minimum amplitude error method for a 3L-NPC-VSI. Compared with the conventional overmodulation strategy based on the minimum amplitude error method, the utilization of the DC-bus voltage is higher. Meanwhile, a virtual space vector modulation strategy is adopted for inverter neutral-point (NP) voltage balance and common-mode voltage (CMV) suppression. Furthermore, the suppression of leakage current also has been verified. Furthermore, the implementation details of the proposed overmodulation strategy based on minimum amplitude error method is elaborated. The effectiveness of the proposed method is verified by simulation and experimental results.