The Superiority of Turbulent Flow of Water-based Optimization for Speed Control of Brushless DC Motor

A Brushless Direct Current Motor (BLDC) is a synchronous motor with trapezoidal/square wave counter-electromotive force, a typical example of highly coupled nonlinear systems. In industrial control, BLDC motor drive usually uses a proportional-integral (PI) controller to control the speed, but it is challenging to adjust the scale factors. In this paper, A novel Turbulent Flow of Water-based Optimization (TFWO) approach, inspired by how water travels in nature, is presented and implemented to control the speed of a BLDC motor by optimizing the PI controller. The speed controller is modified using the Integral of Squared Error (ISE) as the objective function, a time-domain performance index. The proposed optimization technique is compared to other nature-inspired optimization methods, such as Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and Biogeography-Based Optimization (BBO) algorithms, to see its success in optimizing. It has been shown that the suggested technique for optimum adjustment of PI controller coefficients, which is to be positioned in the BLDC motor speed control loop, outperforms all existing algorithms in terms of accuracy and efficiency. The results show that the suggested control technique offers a quicker response time than other control systems and a considerably enhanced response time to fluctuations.