Development a model of an adaptive fuzzy neural network controller for the control system of a synchronous motor with permanent magnet throttle bypass in the ammonia synthesis process
Abstract
In this work, we present an adaptive fuzzy controller utilizing a fuzzy neural network for the control system of a synchronous motor with permanent magnet throttle bypass in the ammonia synthesis process. This approach offers a straightforward design, eliminates the need for a system model, and removes the constraints of a fixed universal range for fuzzy output. By employing a fuzzy neural network, our method can dynamically identify and adjust to the control system, enabling effective adaptation without prior knowledge of the system's dynamics. Mathematical models and algorithms for the control system are developed, integrating motor dynamics with fuzzy logic and neural networks. Simulation and testing show the effectiveness of the proposed control system in regulating motor speed and torque. The study contributes to the advancement of motor control systems in industrial processes.