SUMMARYIn this paper, a shunt active filter based on adaptive linear neuron (ADALINE) method is analyzed. The ADALINE that is used here as the harmonic extraction method is implemented with the measurement of load current under the direct and indirect techniques. The response of method to the loading conditions is compared to that of the instantaneous reactive power theory (IRPT) method. TMS320F2812 digital signal processor (DSP) is employed as a central processing unit in experimental works.
With Predictive Current Controllers, system behavior or current reference is predicted. In this way, it is aimed to prevent hardware and software related delays. In this study, new Artificial Neural Network (ANN) based Predictive Current Controllers are designed using four different methods for voltage source inverters. The training of the networks is done offline using the data obtained from the simulation results for different parameters in the Matlab environment. In the first proposed method, a static ANN based current controller is designed and trained using the data obtained from the Finite Control Set Model Predictive Control (FCS-MPC) method. Then, a feed-forward reference current predictor ANN (PRefNN) is designed to make sinusoidal reference current prediction in the other three methods. The other proposed predictive ANN methods are trained by taking the data offline from the inverter system in which PRefNN and the classical current controllers (Hysteresis, PR, and PI) are used. In this way, three different predictive current controllers named as Hysteresis based predictive ANN (Hist-PNN), PR based predictive ANN (PR-PNN), and PI based predictive ANN (PI-PNN) are designed. Classical current control methods have been given predictive properties with these three different network structures. And also, it is improved the performance of classical methods against parameter changes and noises. A three phase 5kVA inverter circuit with a 7MBP50RJ120 IPM module in the power stage and STM32f407 as a controller is designed for the experimental setup. The methods are tested in simulation and validated in the experimental setup.
In this paper, the program source code of the STM32F407 microcontroller for PV (photovoltaic) inverter circuit was tested using Simulink before applying it to a power electronics circuit. Firstly, a single-phase grid-connected PV (photovoltaic) inverter structure is modeled in Matlab / Simulink environment. In the light of these simulation results, the control blocks of the inverter are programmed using the MikroC ARM compiler for the STM32F407 microcontroller. Before the circuit design stage, a model was developed to work with Matlab / Simulink in order to prevent possible errors and losses of the microcontroller code of the designed PV inverter. This model includes power electronics semiconductors and passive components, PV panels, grid and data communication blocks. The C source code containing the inverter control blocks (MPPT, PLL, DC Link PI and Current controller) are loaded into the STM32F4 Discovery kit. At each step of the simulation, the current and voltage information obtained from the Matlab model is sent to the STM32F4 kit via serial communication. The current and voltage information is processed in microcontroller software and switching pulses of IGBTs are created and transferred back to Matlab model. In this way, a rapid and secure prototype hardware development method is presented with the joint operation of Matlab and STM32F4. The results obtained from the simulation and Matlab-STM32F4 joint study are given comparatively.
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