Mostafa Mosa

An improved MPPT technique for high gain DC-DC converter using model predictive control for photovoltaic applications

This paper presents an enhanced Maximum Power Point Tracking (MPPT) of Photovoltaic (PV) systems by means of Model Predictive Control (MPC) techniques. The PV array can feed power to the load through a DC/DC converter boosting the output voltage. Due to stochastic behavior of solar energy, MPPT control technique of PV arrays is required to operate at maximum power point. Extracting the maximum power from PV systems has been widely investigated within the literature. The main contribution of this paper is enhancement of the Incremental Conductance (INC) method through a fixed step predictive control under measured fast solar radiation variation. The proposed predictive control to achieve Maximum Power Point (MPP) speeds up the control loop since it predicts error before the switching signal is applied to the selected high gain multilevel DC-DC converter. Comparing the developed technique to the conventional INC method shows significant improvement in PV system performance. Experimental validation is presented using the dSpace CP 1103 to implement the proposed MPC-MPPT.

High performance predictive control applied to three phase grid connected Quasi-Z-Source Inverter

Model predictive control has emerged as a very powerful method for controlling of electrical energy. One of the major advantages for this control is the performance of the power converters become more better comparing with the traditional modulation control techniques. In this paper, a model predictive control is used to drive a three phase grid connected Quasi-Z-Source Inverter (qZSI) to improve the performance of the three phase injected output current. This technique uses a model of the qZSI and capacitor voltage, input inductor current and AC three phase output load currents to predict the behavior of the measured parameters. The resulting closed-loop system achieves high dynamic performance for all controlled parameters. The total system has been analyzed, simulated by using MATLAB/SIMULINK program then implement by using dSPACE 1103 to prove the idea.

Model Predictive Control applied for Quasi-Z-source inverter

This paper presents a Model Predictive Control (MPC) algorithm applied to a Quasi-Z-source inverter (qZSI). This control is based mainly on the measurement of the qZSI capacitor voltage and the AC load currents. These measured values are used to predict the future values of the capacitor voltage and load current. This task is based on the determination of each possible voltage vector generated by the qZSI which can ensure the tracking of the capacitor voltage and the output current references. This control is implemented under MATLAB/SIMULINK program; the obtained results are validated with real time simulation using dSPACE 1103 ControlDesk. The real time simulation results have been provided for principle validation.

Modified MPPT with using model predictive control for multilevel boost converter

This paper proposes a modification in the maximum power point tracking (MPPT) by using model predictive control (MPC). The modification scheme of the MPPT control is based on the perturb and observe algorithm (P&O). This modified control is implemented on the dc-dc multilevel boost converter (MLBC) to increase the response of the controller to extract the maximum power from the photovoltaic (PV) module and to boost a small dc voltage of it. The total system consisting of a PV model, a MLBC and the modified MPPT has been analyzed and then simulated with changing the solar radiation and the temperature. The proposed control scheme is implemented under program MATLAB/SIMULINK and the obtained results are validated with real time simulation using dSPACE 1103 ControlDesk. The real time simulation results have been provided for principle validation.

Model predictive control of a grid connected quasi-Z-source inverter

The Z-source inverter (ZSI) is a recently proposed single stage converter topology with buck-boost capabilities. The quasi-Z-source inverter (qZSI) has been developed which features several improvements when compared to the traditional ZSI. Control strategies of the ZSI and qZSI are important issue and several feedback control strategies have been investigated so far. This paper presents a model predictive control (MPC) of a grid connected qZSI, where the grid current is properly controlled during transient and steady state operation by including inductor current, capacitor voltage as well as switching frequency as additional control constrains. Both steady-state and transient results show high performance response of the proposed control technique.

A novel FPGA implementation of a model predictive controller for SiC-based Quasi-Z-Source inverters

This paper proposes a novel implementation of an FPGA-Based Model Predictive Control (MPC) for a SiC Quasi-Z-Source inverter. To speed-up computations, to satisfy the control requirements and to increase the switching frequency, an MPC algorithm is designed for parallel processing and is implemented on an FPGA. This is suitable for high-sampling/switching frequency operation that enables the use of MPC in fast systems as SiC-based converters. Proposed concepts are simulated by MATLAB Simulink and are experimentally validated using a three-phase SiC-based Quasi-Z-Source inverter. Both of simulation and experimental results show that the proposed FPGA-based controller attains a good performance at a very small calculation time, comparable to that consumed by conventional MPC sequential implementations.

Finite set model predictive current control with reduced and constant common mode voltage for a five-phase voltage source inverter

Multiphase drives are now becoming serious competitor to traditional three-phase drives due to reasons of better fault tolerant property and reduced per-phase converter rating that are especially suited to high power drives application. One of the major factor of widespread research on multiphase drive are the availability of high computational power of control platforms such as DSP and FPGAs. With availability of such computationally powerful tool of DSP/FPGA leads to the adoption of model predictive control (MPC) in electric drive. This paper present current control of a five-phase inverter using MPC with the aim of achieving constant common mode voltage. By achieving constant common mode voltage (CMV), bearing current can be greatly reduced. This is achieved by proper selection of space vectors and analysis of drop in voltage gain is presented. Simulation results are supported by experimental approach.