Abstract
Artificial Intelligence-Based Optimal PID Controller Design for BLDC Motor with Phase Advance
Highlights
The brushless direct current (BLDC) motor is a kind of synchronous motor having permanent magnets on the rotor and stator winding
Results obtained from the adaptive tabu search (ATS) and intensified current search (ICS) will be compared with Ziegler-Nichols (ZN) tuning rule [28],[29] and genetic algorithm (GA) [30]
The artificial intelligence (AI)-based optimal PID controller design optimization for BLDC motor speed control with phase advance has been presented in this paper
Summary
The brushless direct current (BLDC) motor is a kind of synchronous motor having permanent magnets on the rotor and stator winding. The speed response of the BLDC motor system with phase advance can be done effectively by optimizing the values of PID controller parameter using artificial intelligence (AI) algorithms. The applications of AI algorithms for PID controller of the BLDC motor system with phase advance have not been presented in the previous researches [4], [8]-[11]. This paper presents the use of AI algorithms for tuning the PID parameters (KP, Ki and Kd) for controlling the BLDC motor with phase advance. Phase advance The phase advance technique is a common control of the phase current to lead the phase back emf It can increase the speed of BLDC motor over the base speed. The proposed drive system composes of three phase inverter, switch control signals, Hall effect sensors, BLDC motor and DC voltage source.
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