This paper proposes a robust nonlinear predictive current control (RNPCC) method for permanent magnet synchronous motor (PMSM) drives, which can optimize the current control loop performance of the PMSM system with model parameter perturbation. First, the disturbance caused by parameter perturbation was considered in the modeling of PMSM. Based on this model, the influence of parameter perturbation on the conventional predictive current control (PCC) was analyzed. The composite integral terminal sliding mode observer (SMO) was then designed to estimate the disturbance caused by the parameter perturbation in real time. Finally, a RNPCC method is developed without relying on the mathematical model of PMSM, which can effectively eliminate the influence of parameter perturbation by injecting the estimated disturbance value. Simulations and experiments verified that the proposed RNPCC method was able to remove the current error caused by the parameter perturbation during steady state operation.

Aiming at the problem of large magnitude and high frequency of common-mode voltage (CMV) when space vector pulse width modulation (SVPWM) is used in a three-phase motor fed by a two-level voltage source inverter, a common-mode reduction SVPWM (CMRSVPWM) is studied. In this method, six new sectors are obtained by rotating six sectors of conventional SVPWM by 30°. In odd-numbered sectors, only three non-zero vectors with odd subscripts are used for synthesis, while in even-numbered sectors, only three non-zero vectors with even subscripts are used for synthesis. The actuation durations of three non-zero vectors in each switching period in each sector are given. Simulation and experimental results show that, compared with the conventional SVPWM, the CMV magnitude of CMRSVPWM is reduced by 66.67% and the CMV frequency of CMRSVPWM is reduced from the original switching frequency to the triple fundamental frequency. At the same time, the current, torque and speed of the motor are still good.

In inverters based on a single proportional-integral (PI) or deadbeat (DB) controller, an inherent resonance peak may emerge near their current loop cutoff frequency, which results in harmonic amplification or even resonance. Additionally, inappropriate filter circuits implemented in sampling circuits may result in the expansion of the resonance peak. Thus, this paper further investigates the influence of the sampling circuits on a PI-or DB-based control loop. Then, the RC filter in the sampling circuit is designed to reduce the inherent resonance peak. Moreover, a compound control strategy based on an improved repetitive controller (IRC) plus a PI controller is adopted for the grid-side converter of a direct-drive wind system. This strategy enhances the harmonic and reactive compensation performance by reconstructing the internal model of the classic repetitive controller (CRC) and limiting the bandwidth of the PI-based loop to a low level. The parameters of the presented IRC-plus-PI control are designed for the purpose of resonance peak elimination and system stability. Furthermore, the non-integer delay problem is solved with an inserted fraction compensator (FC), which plays the role of a low-pass filter in the IRC. Finally, the feasibility and effectiveness of the presented control method is verified by the experimental results.

This paper proposes an optimal reactive power control method to maximize wind farm revenue and minimize the total electrical losses of a doubly-fed induction generator (DFIG)-based wind farm. Specifically, the split Bregman method is used to solve the optimal control problem in a distributed manner. That is, the optimization problem is decomposed into sub-problems by the optimal distributed control strategy, and each sub-problem is solved independently in each local controller through the parallel method, which reduces the calculating burden and improves the information privacy. Thus, when a fault occurs, the proposed distributed control strategy can overcome the system fault and improve the reliability and security of the system. Furthermore, an economic financial model of annual revenue is contributed to examine the income impact with or without certified emission reduction (CER) by the clean development mechanism (CDM). Compared with the dual ascent (DA) method, sequential quadratic programming (SQP) method and the proportional dispatch method (PDM), the annual revenue (AR) of the wind farm using the proposed split Bregman method is the highest. Simulation results demonstrate that this method has promising performance in both optimization quality and computational efficiency.

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