Comparative Analysis Of The Performance Of Vector And Neural Controls For Industrial Applications: Case Of A Flour Mill

This article compares the performance of classical vector control and neural control for asynchronous motors, which are essential in industry. Improving the control of these motors is crucial for optimizing their performance and efficiency. While various control strategies have been explored, gaps remain in terms of robustness, stability, and speed, especially when comparing classical and intelligent methods. The objective of the study is to analyze and compare these two approaches to determine which one offers the best performance in an industrial context. Simulations conducted in Matlab/Simulink show that neural control outperforms vector control in terms of regulation, stability, and responsiveness, paving the way for future research on optimizing intelligent control systems.