This project focuses on designing and analyzing a neural network–based PID controller to optimize the speed control of a Brushless DC (BLDC) motor. We develop both a conventional PID controller and an ...

Abstract: In this paper, the fuzzy control and the PID control are combined, and the fuzzy inference method is utilized to realize the on-line auto-tuning of PID parameters. By applying the fuzzy ...

1 Faculty of Electrical Technology and Engineering (FTKE), Universiti Teknikal Melaka Malaysia, Melaka, Malaysia. 2 Institut Matematik Kejuruteraan (IMK), Universiti Malaysia Perlis (UniMAP), Perlis, ...

Abstract: In an autonomous driving system, the degree of control of the vehicle's speed and direction is a crucial factor in reflecting its safety and stability. Traditional PID controllers have ...