Fuzzy Systems

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ANFIS based Controller with Regenerative Braking System for an Electric Vehicle


Affiliations
1 Department of Electrical and Electronics Engineering, Jyothi Engineering College, Cheruthuruthy, Thrissur, India
     

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The electronically commutated Brushless DC motors are widely used in many industrial applications which increase the need for design of efficient control strategy for these motors. This paper deals with the efficient control mechanisms for these drives using meaningful fuzzy sets and rules. The proposed system includes a Brushless DC motor control utilizing the PID control, and improved performance via adaptive Neuro based fuzzy control. It uses a battery to store the regenerated energy. An adaptive Neuro fuzzy inference system is developed using MATLAB. Simulation results show that ANFIS reaches to the target faster and overcomes the complexity of the problem.


Keywords

Brushless DC (BLDC) Motor, Fuzzy Control, Proportional-Integral-Derivative (PID) Control, Adaptive Neuro Based Fuzzy Inference System (ANFIS), Regenerative Braking System (RBS).
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  • ANFIS based Controller with Regenerative Braking System for an Electric Vehicle

Abstract Views: 257  |  PDF Views: 1

Authors

M. Akhila
Department of Electrical and Electronics Engineering, Jyothi Engineering College, Cheruthuruthy, Thrissur, India
P. Ratnan
Department of Electrical and Electronics Engineering, Jyothi Engineering College, Cheruthuruthy, Thrissur, India

Abstract


The electronically commutated Brushless DC motors are widely used in many industrial applications which increase the need for design of efficient control strategy for these motors. This paper deals with the efficient control mechanisms for these drives using meaningful fuzzy sets and rules. The proposed system includes a Brushless DC motor control utilizing the PID control, and improved performance via adaptive Neuro based fuzzy control. It uses a battery to store the regenerated energy. An adaptive Neuro fuzzy inference system is developed using MATLAB. Simulation results show that ANFIS reaches to the target faster and overcomes the complexity of the problem.


Keywords


Brushless DC (BLDC) Motor, Fuzzy Control, Proportional-Integral-Derivative (PID) Control, Adaptive Neuro Based Fuzzy Inference System (ANFIS), Regenerative Braking System (RBS).