Zhenbin Zhang

Predictive Control With Novel Virtual-Flux Estimation for Back-to-Back Power Converters

This work proposes and experimentally verifies a novel virtual flux (VF) estimation method for the predictive control of back-to-back voltage-source power converters with a space vector modulator (SVM). The novelty of the proposed approach is the development of a time domain initial bias compensation virtual flux (IBC-VF) estimation method and its combination with a predictive control scheme with constant switching frequency. Theoretical analysis and implementation procedures of the proposed method are developed in detail. Compared to two conventional bandpass filter-based VF estimation methods, the proposed IBC-VF method shows a much faster dynamic response. The whole IBC-VF-based predictive control scheme is realized in the

An Encoderless Predictive Torque Control for an Induction Machine With a Revised Prediction Model and EFOSMO

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Sensorless Control for SPMSM With Concentrated Windings Using Multisignal Injection Method

frame and so does not require Parks transformation. The proposed control scheme is implemented on a commercial off-the-shelf field-programmable-gate-array-based platform. By using a single-cycle timed loop (SCTL) technique, the whole computation is finished within 2.6

FPGA-Based Experimental Investigation of a Quasi-Centralized Model Predictive Control for Back-to-Back Converters

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Encoderless model predictive control of back-to-back converter direct-drive permanent-magnet synchronous generator wind turbine systems

, making the compensation of the calculation time obsolete. Both simulation and experimental results emphasize the effectiveness of the proposed scheme.

Novel ripple reduced Direct Model Predictive Control of three-level NPC active front end with reduced computational effort

The finite control state predictive torque control (FCS-PTC) method is known to produce a fast response. However, when compared with the direct torque control (DTC) method, which is inherently encoderless, the FCS-PTC method has a disadvantage because of its speed dependence. An encoderless FCS-PTC method that is based on a revised prediction model for an induction machine is proposed and experimentally verified in this paper. To observe the unmeasured variables, an encoderless full-order sliding-mode observer (EFOSMO) is applied. Neither the revised prediction model nor the EFOSMO uses the estimated rotor speed value. The disturbance injected by process of speed estimation in the usual encoderless predictive methods is removed from the system. The experimental results show that the proposed algorithm can work well and achieve good performance at a very wide range of speeds.

Model predictive torque control with an extended prediction horizon for electrical drive systems

Surface-mounted permanent magnet synchronous machine with concentrated windings (cwSPMSM) is a high-performance drive machine and has been adopted in many applications. The difficulty of implementing its sensorless control at low and zero speeds is its multiple saliencies, which is much more significant than most other ac machines. The traditional decoupling methods provide successful results only under the condition that high-order saliencies are not stronger than half of the primary saliency. Furthermore, the behavior of the multiple saliencies is principally frequency dependent. Based on the characteristics of such machines, this paper proposes a multisignal injection method for realizing sensorless control. This method injects multiple high-frequency signals with different frequencies and magnitudes into the machine. Different frequency components in the response current signals are demodulated and then combined together to get the clear primary saliency signal, which is used to identify the rotor position. This new method was validated using a cwSPMSM at low speed. The experimental results proved the effectiveness and accuracy of the new method.

Two direct torque and power control methods for back-to-back power converter PMSG wind turbine systems

Voltage source back-to-back power converters are widely used in grid-tied applications. This paper presents a quasi-centralized direct model predictive control (QC-DMPC) scheme for back-to-back converter control without a dc-link outer-loop controller. Furthermore, the QC-DMPC is experimentally compared with a conventional proportional-integration (PI) dc-link controller-based DMPC (PI-DMPC) scheme. For the QC-DMPC scheme, the dc-link voltage is directly controlled by a grid-side predictive controller using a dynamic reference generation concept and load-side power estimation. For the PI-DMPC scheme, the dc-link voltage is controlled by an external PI controller. Both schemes are implemented on a field programmable gate array (FPGA)-based platform. Effectiveness of the proposed QC-DMPC is verified by both simulation and experimental data. Moreover, FPGA implementation issues (resource usage and timing information), dc-link control performance, and robustness to parameter variation of the two DMPC schemes are compared in detail. The results emphasize that the QC-DMPC may outperform the PI-DMPC scheme in normal operation but with a slightly higher usage of FPGA resources. However, PI-DMPC scheme is more robust when parameter variations are considered.

FPGA HiL simulation of back-to-back converter PMSG wind turbine systems

This paper presents encoderless model predictive control scheme with time-varying sliding mode observer for a complete wind turbine system. The wind turbine system consists of a back-to-back converter (AC/DC/AC) and a direct-drive permanent-magnet synchronous generator (PMSG). We give a complete model of the system and present encoderless fixed-frequency model predictive direct torque control of the generator and finite-set model predictive direct power control of active and reactive power on the grid side. The sliding mode observer utilizes a time-varying switching gain and a time-varying cut-off frequency to estimate rotor position and rotor speed without chattering. The proposed strategy is illustrated by simulations as a first proof of concept. The simulation results show that the proposed strategy achieves fast torque control dynamics and highly decoupled control of active and reactive power.

Fully FPGA based direct model predictive power control for grid-tied AFEs with improved performance

Three-level neutral-point clamped (NPC) power converter seems promising for high power grid-tied renewable applications. Direct Model Predictive Control (DMPC) is an attractive control method, in particular for multi-level converters. However, relatively big ripples of the control variables and heavy computational efforts are regarded as two of the shortcomings for DMPC schemes due to its cost enumeration and one-vector-per-control-interval characters. This work proposes a computational efficient ripple-reduced DMPC scheme for three level NPC Active-Front-End (AFE). By combining a deadbeat concept the targeted switching vectors are allocated efficiently and the respective actuating times of the vectors are on-line optimally calculated. Compared to the classical DMPC scheme, computational efforts are reduced efficiently and much smaller ripples of the control variables are achieved. Simulation results emphasize the effectiveness of the proposed scheme.