A Novel Virtual Vector Modulation-based scheme of Model Power Predictive for VIENNA Rectifier

When the finite control set model predictive(FCS-MPC) algorithm is applied to the three-level converter, there are problems such as large current harmonics, high requirements for the computing efficiency of the micro-controller, complex multi-objective optimization and limited output vector switching. In additional, the mismatch of inductance parameter may directly affect the observation accuracy of FCS-MPC. Furthermore, due to the limitation of finite set model prediction, it leads to the switching operation is not constant and the decrease of the grid-connected current quality. In this regard, an improved model predictive direct power control based on the combined virtual vector modulation (MPDPC-VM) is proposed by considering the influence of the filter inductance parameter mismatch. The finite control set and restricted vector switching of the Vienna rectifier are modeled to avoid excessive voltage jumps, and the predicted values of input power is obtained by the sliding-mode control (SMC) strategy. Then, a linear synthesis method of virtual vector modulation-based scheme is proposed, which increases the number of the available voltage vectors in a single switching period from 8 to 19. The grid-connected current ripple is improved by reducing the error between the expected voltage vector and the available voltage vector. Finally, the model reference adaptive system (MRAS) method is applied to improve the working reliability and reduce the influence of mismatching of inductance parameters. Extensive simulation and matching experimental results is given to demonstrate the validity of the proposed strategy under steady-state and transient responses conditions compared against the existing FCS-MPC

Stability analysis of high power factor Vienna rectifier based on reduced order model in d-q domain

Abstract For a DC distributed power system, system stability can be predicted by dividing it into source and load subsystems, and then applying the Nyquist criterion to the impedance interaction between the source and load model. However, the generalized Nyquist criterion is extremely complicated and cannot directly reveal effective control strategies to reduce interaction problems of cascade three-phase AC systems. Specifically, as a current force rectifier, this characteristic makes it difficult to judge the stability of a cascade three-phase Vienna AC system. To deal with the aforementioned problems, a simplified small signal stability criterion is presented for an AC distributed power system. Based on the criterion, the small signal model and impedance based on the reduced order model in the d-q domain are studied theoretically. For the instability issue, an impedance regulator design method is presented. The correctness of the simplified stability criterion and the effectiveness of the proposed impedance regulator method are validated by extensive simulation and experiment

High-Precision Lens-Less Flow Cytometer on a Chip

We present a flow cytometer on a microfluidic chip that integrates an inline lens-free holographic microscope. High-speed cell analysis necessitates that cells flow through the microfluidic channel at a high velocity, but the image sensor of the in-line holographic microscope needs a long exposure time. Therefore, to solve this problem, this paper proposes an S-type micro-channel and a pulse injection method. To increase the speed and accuracy of the hologram reconstruction, we improve the iterative initial constraint method and propose a background removal method. The focus images and cell concentrations can be accurately calculated by the developed method. Using whole blood cells to test the cell counting precision, we find that the cell counting error of the proposed method is less than 2%. This result shows that the on-chip flow cytometer has high precision. Due to its low price and small size, this flow cytometer is suitable for environments far away from laboratories, such as underdeveloped areas and outdoors, and it is especially suitable for point-of-care testing (POCT)

Model predictive direct power control scheme for Vienna rectifier with constant switching frequency

Abstract Model predictive direct power control (MPDPC) has strong robustness and fast dynamic response, so it is widely applied in the control system of grid‐connected converter. However, the traditional FCS‐MPC bears with variable switching state, which will reduce the current tracking accuracy, accidentally produce current ripple and electromagnetic noise. Here, a double closed‐loop control strategy with constant switching frequency based on optimal switching sequence synthesis of model predictive direct power control (MPDPC‐CF) in the inner loop and SMC control in the outer loop is proposed for the non‐linear system of Vienna rectifier. Firstly, the Vienna rectifier is modelled to obtain the predicted values of input power. Then, the given values of active power and reactive power are obtained through the outer loop. Three adjacent voltage vectors with the lowest cost function in the sector are selected to synthesize the optimal voltage vector, and the pulse time of the corresponding vector is calculated according to the cost function of the voltage vector. To verify the correctness of the theoretical analysis, the Vienna rectifier is taken as the research object, and the comparison with the traditional MPDPC shows that the proposed constant frequency model predictive control has good steadystate and dynamic performance

Model predictive control for Vienna rectifier with constant frequency based on inductance parameters online identification

When the finite control set model predictive control (FCS-MPC) is applied to the three-level converter, there are problems such as large current harmonics, high requirements for the computing efficiency of the microcontroller, complex multi-objective optimization and limited output vector switching. In addition,the mismatch of inductance parameter may directly affect the observation accuracy of FCS-MPC. To solve the above problem,a double vector model predictive control strategy with constant frequency strategy based on the inductance parameters on-line identification is presented.First, a single objective cost function based on the direct power is constructed by optimizing the redundant vector which is selected to balance the neutral-point potential, the design of weighting factor is avoided.At the same time, in order to effectively reduce the grid current ripple under single vector modulation, space vector pulse width modulation (SVPWM) is realized by combining with zero vector control mode. And, a parameter identification method based on model reference adaptive system(MARS) is proposed to overcome the effect of model parameter mismatch.Finally, the results show that the proposed F-MPCCF has good steady-state and dynamic performance from the static, transient and neutral-point potential control