Call For Paper Volume:7 Issue:9 Sep'2020 |

ADAPTIVE CONTROL THEORY AND RECURRENT NEURAL NETWORK BASED BLDC CONTROL SYSTEM

Publication Date : 15/09/2020


DOI : 10.21884/IJMTER.2020.7054.TJ6CF

Author(s) :

Prathap.g , P C . Sivakumar.


Volume/Issue :
Volume 7
,
Issue 9
(09 - 2020)



Abstract :

Competitive advantages over AC motors make for DC motors to replace other electrical motors in applications stretching from high-speed automation to electric motorbikes. BLDC drives are very popular in many industries, at present automation are added standard, Virtual Z-source multilevel is a respectable optimal that can boost the output voltage of the drive. An novel soft computing based Recurrent Neural Network (RNN) based Virtual Z-source multilevel inverter, for BLDC motor drive control to make the system balanced when the load is unbalanced and to reduce the electrical torque pulsation. In this paper, the utilization of the RNN to tackle the selective harmonic elimination issue in INVERTER inverters is proposed. This strategy permits active voltage control of the crucial and besides concealment of a particular set of harmonics. The favorable principle position of the proposed technique is that it requires delicate processing switching angles. The scheme was actualized to assess its execution in the disposal of sounds in a inverter. The performance is evaluated in various emphasis levels of the different control models. From the outcomes, it has been demonstrated that the proposed method can achieve a reduced harmonics by relieving the predominant odd order harmonics. The results investigation has shown that the proposed RNN switching angles can keep away the higher order harmonics. Thus the created voltage waveform can keep up its harmonics free inverter. By utilizing the got Switching edges, the harmonics can be maintained a strategic distance. Thus the subjected inverter nourished BLDC can offer with not very many hazard components to the utilities. The proposed concept is analysed and implemented with MATLAB/SIMULINK software. The simulation results verify the correctness of the theories and the effectiveness of the proposed approach.


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ADAPTIVE CONTROL THEORY AND RECURRENT NEURAL NETWORK BASED BLDC CONTROL SYSTEM

September 2, 2020