Is it possible to implement the maximum power point tracking (MPPT) system in the solar cell using artificial intelligence algorithms in FPGA through Vitis AI?
Yes it obvious, and you can formulate the maximum power point tracking (MPPT) system as transfer function or input to output representation and hence to computation setting via MATLAB or Python etc. See it e.g., in Simulink https://au.mathworks.com/solutions/power-electronics-control/mppt-algorithm.html
But I mean using the Vitis Ai tool to implement MPPT hardware on FPGA without using low-level languages like VHDL or Verilog.
The Vitis AI development environment is Xilinx’s development platform for AI inference on Xilinx hardware platforms, including both edge devices and Alveo cards. It consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP.
I have implemented a CNN convolution neural network via Vitis Ai on the zcu104 board. I wanted to know if it is possible to use Vitis Ai tools in the field of solar panels or not? Because I haven't seen anything in this field so far.
The processing core of each board is different from the other board,
There are two ways to implement FPGA, one is to implement the kernel with our own low-level languages such as HLS or HDL, or to use ready-made kernels for neural network use, I do not know Intel, but Xilinx for AI use, offers a package called Vitis Ai, which includes the libraries needed to implement the high-level neural network, which, with its firmware, connects to a computing core called the DPU, developed by Xilinx itself. Executes the kernels you implemented at the top level on the DPU.
So, I wanted to know is possible for this work with the PV panel and implement the artificial intelligence algorithm mppt or not!
Yes indeed, please you may try booth or may be more approaches, finally you will see which method is more tractable with best possible outcomes. As far as AI is concern, please do not be confuse in its wordings. All input to output computational models/algorithms/functions are core bodies of Machine Learning (ML), and ML is a subset of Artificial Intelligence (AI).
Deep Learning (DL) is an application of ML for training data, so DL is the subset of ML.
Zahra Tohidinejad means whether there is a common ground between the artificial intelligence algorithms supported by Vitis AI and the artificial intelligence algorithms useful for MPPT? However, this question is expressed as application-based.