Showing 4 results for Mpc
M. Oloumi, R. Ghazi, M. Monfared,
Volume 11, Issue 2 (6-2015)
Abstract
This paper provides a detailed comparative study concerning the performance of min-projection strategy (MPS) and model predictive control (MPC) systems to control the three-phase grid connected converters. To do so, first, the converter is modeled as a switched linear system. Then, the feasibility of the MPS technique is investigated and its stability criterion is derived as a lower limit on the DC link voltage. Next, the fundamental equations of the MPS to control a VSC are obtained in the stationary reference frame. The mathematical analysis reveals that the MPS is independent of the load, grid, filter and converter parameters. This feature is a great advantage of MPS over the MPC approach. However, the latter is a well-known model-based control technique, has already developed for controlling the VSC in the stationary reference frame. To control the grid connected VSC, both MPS and MPC approaches are simulated in the PSCAD/EMTDC environment. Simulation results illustrate that the MPS is functioning well and is less sensitive to grid and filter inductances as well as the DC link voltage level. However, the MPC approach renders slightly a better performance in the steady state conditions.
J. Fallah Ardashir, M. Sabahi, S. H. Hosseini, E. Babaei, G. B. Gharehpetian,
Volume 13, Issue 2 (6-2017)
Abstract
This paper proposes a new single phase transformerless Photovoltaic (PV) inverter for grid connected systems. It consists of six power switches, two diodes, one capacitor and filter at the output stage. The neutral of the grid is directly connected to the negative terminal of the source. This results in constant common mode voltage and zero leakage current. Model Predictive Controller (MPC) technique is used to modulate the converter to reduce the output current ripple and filter requirements. The main advantages of this inverter are compact size, low cost, flexible grounding configuration. Due to brevity, the operating principle and analysis of the proposed circuit are presented in brief. Simulation and experimental results of 200W prototype are shown at the end to validate the proposed topology and concept. The results obtained clearly verifies the performance of the proposed inverter and its practical application for grid connected PV systems.
A. Younesi, S. Tohidi, M. R. Feyzi,
Volume 14, Issue 3 (9-2018)
Abstract
Model-based predictive control (MPC) is one of the most efficient techniques that is widely used in industrial applications. In such controllers, increasing the prediction horizon results in better selection of the optimal control signal sequence. On the other hand, increasing the prediction horizon increase the computational time of the optimization process which make it impossible to be implemented in real time. In order to solve this problem, this paper presents an improved strategy in the field of nonlinear MPC (NMPC) of the permanent magnet synchronous motor (PMSM). The proposed method applies a sequence of reduction weighting coefficients in the cost function, over the prediction horizon. By using the proposed strategy, NMPC give a more accurate response with less number of prediction horizon. This means the computational time is reduced. It also suggests using an incremental algorithm to reduce the computational time. Performance of the proposed Nonlinear MPC (NMPC) scheme is compared with the previous NMPC methods via simulations performed by MATLAB/Simulink software, in permanent magnet synchronous motor drive system. The results show that the use of proposed structure not only lowers prediction horizon and hence computational time, but also it improves speed tracking performance and reduces electromagnetic torque ripple. In addition, using the incremental algorithm also reduces the computational time which makes it suitable for real-time applications.
Azzedine Khati,
Volume 20, Issue 3 (9-2024)
Abstract
In this research paper, a multivariable prediction control method based on direct vector control is applied to command the active power and reactive power of a doubly-fed induction generator used into a wind turbine system. To obtain high energy performance, the space vector modulation inverter based on fuzzy logic technique (fuzzy space vector modulation) is used to reduce stator currents harmonics and active power and reactive power ripples. Also the direct vector control model of the doubly-fed induction generator is required to ensure a decoupled control. Then its classic proportional integral regulators are replaced by the multivariable prediction controller in order to adjust the active and reactive power. So, in this work, we implement a new method of control for the doubly-fed induction generator energy. This method is carried out for the first time by combining the MPC strategy with artificial intelligence represented by Fuzzy SVM-based converter in order to overcome the drawbacks of other controllers used in renewable energies. The given simulation results using Matlab software show a good performance of the used strategy, particularly with regard to the quality of the energy supplied.
