• Shital B. Bhadade
• Suyog Hirve

This paper presents the design and performance analysis of Model Reference Neural Network Adaptive (MRNNA) controller for the speed control of Brushless Direct Current motor (BLDC). The behavior of BLDC motor drive is nonlinear so it is complex to handle by using conventional controller such as proportional-integral (PI), proportional-integral-derivative (PID) controller. The interest in emerging Artificial Intelligent (AI) controller for speed control of BLDC motor has been increased. In ANN (Artificial Neural Network) controlling method available data is the result of measuring the dynamic behavior of the system. To solve problem of nonlinearity and parameter variations caused by load and obtain the control scheme that have good dynamic responses model reference neural network adaptive control concept is applied. The controller is intended to track the variations of speed references and stabilizes the output speed during variations in the load. The effectiveness of this proposed method is established by developing simulation model in MATLAB/simulation.

BLDC motor, Artificial Neural Network, Model Reference Adaptive Control, MATLAB simulation model.

"A Speed Control of BLDC Motor by Using Model Reference Neural Network Adaptive Controller", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.286-291, May-2019, Available :http://www.jetir.org/papers/JETIR1905942.pdf

"A Speed Control of BLDC Motor by Using Model Reference Neural Network Adaptive Controller", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp286-291, May-2019, Available at : http://www.jetir.org/papers/JETIR1905942.pdf